Data Entry Jobs in Qatar

Role Purpose<br><br>The Business Data & Analytics Consultant translates client questions and operational needs into trusted analytical requirements, indicators, analyses and decision-support products. The role helps stakeholders define the decision to be supported, identify required data, agree calculation logic and interpret results with appropriate context, quality and governance controls.<br><br>The consultant works across business and technical teams, connecting subject-matter expertise with data architecture, engineering, metadata, quality and visualisation. Work may include use-case development, requirements elicitation, indicator design, exploratory analysis, dashboard specifications, acceptance testing and insight communication. The role does not own the client's decisions; it provides transparent evidence and explains assumptions, limitations and implications so authorised stakeholders can act confidently.<br><br>Key Responsibilities<br><br>Elicit and document the business questions, decisions, users, outcomes and constraints for analytical use cases. Translate stakeholder needs into data, calculation, indicator, reporting and acceptance requirements. Identify source datasets, definitions, owners, quality conditions, time periods and required transformations. Develop use-case charters, analytical requirements, indicator definitions and traceability records. Perform exploratory analysis and validate patterns, exceptions and limitations with subject-matter experts. Define calculation logic, dimensions, filters, targets, frequency and interpretation guidance for indicators. Work with engineers, architects and visualisation specialists to ensure requirements are implementable and testable. Specify dashboard, report and data-product behaviour from a business and user perspective. Support user acceptance testing and verify that outputs reconcile to definitions and trusted sources. Communicate findings through clear narratives, tables, visuals and decision-focused recommendations. Document data-quality caveats, assumptions, confidence limits and responsible-use considerations. Train client users to interpret outputs correctly and maintain requirements and indicator definitions.<br><br>Minimum Requirements<br><br>Education<br><br>Bachelor's degree in analytics, statistics, economics, information systems, business or a related field. An equivalent combination of relevant education and directly applicable consulting or implementation experience may be considered.<br><br>Professional Experience<br><br>Typically 3-7 years in business analysis, data analysis, performance management or analytics. Experience in business analysis, data analysis, analytics, reporting or decision-support work. Experience eliciting requirements and translating business questions into data and analytical specifications. Experience validating indicators, dashboards, reports or analytical products with users. Exposure to government services, operational performance or policy analysis is preferred.<br><br>Technical and Domain Knowledge<br><br>Business-analysis and requirements-management techniques. Analytical use-case and indicator design. Data sourcing, definitions, dimensions, calculations and validation. Exploratory analysis using SQL, spreadsheets or analytical tools. Dashboard and report requirements and user-acceptance criteria. Data quality, metadata, lineage and responsible-use considerations. Benefits, outcomes and decision-support measurement. Clear analytical documentation and data storytelling.<br><br>Core Competencies<br><br>Requirements analysis. SQL and data analysis. Indicator design. Data storytelling. Business process knowledge. Quality and metadata awareness. Business curiosity. Requirements precision. User focus. Interviewing stakeholders and clarifying ambiguous questions. Facilitating use-case, indicator and requirements workshops. Translating between business and technical teams. Presenting evidence, assumptions and limitations without overclaiming. Producing decision-ready analysis and professional reports. Managing feedback, revisions and acceptance criteria. Teaching client users how to interpret and maintain analytical outputs.<br><br>Preferred Certifications<br><br>CBAP or PMI-PBAMicrosoft Power BI Data Analyst Associate CDMP Associate<br><br>Focus areas<br><br>Requirements analysis SQL and data analysis Indicator design<br><br>Ready to apply for this role?<br><br>Apply for Business Data & Analytics Consultant

Role Purpose<br><br>The Data & Digital Quality Assurance Consultant provides independent delivery assurance for client data products, analytics solutions, integrations, platforms and related digital components. The role verifies that requirements are testable, that delivered functions behave as intended and that data, controls, performance, security and user experience are supported by adequate evidence.<br><br>The consultant works with business analysts, engineers, developers, architects, platform teams and client users to plan and execute risk-based testing. It distinguishes confirmed defects from assumptions, maintains traceability and supports objective acceptance decisions. The role may recommend whether a deliverable is ready, but formal acceptance remains with authorised client stakeholders. Effective candidates combine testing discipline with strong communication, data awareness and the ability to identify defects that arise across functional, data and integration boundaries.<br><br>Key Responsibilities<br><br>Review requirements, user stories, acceptance criteria, designs and controls for completeness, clarity and testability. Develop risk-based test strategies, plans, scenarios, cases, data, environments and evidence requirements. Maintain traceability between requirements, test cases, results, defects and acceptance decisions. Test data pipelines, transformations, APIs, integrations, reports, dashboards and platform functions. Validate calculations, reconciliations, data-quality rules, reference data, metadata and error handling. Assess functional, regression, integration, usability, performance and selected security-control behaviour. Record defects with reproducible steps, evidence, impact, severity and clear expected results. Coordinate defect triage, retesting, regression testing and closure evidence with delivery teams. Support user acceptance testing through scripts, training, evidence capture and issue management. Identify opportunities for repeatable or automated testing without weakening manual judgement. Prepare quality dashboards, readiness assessments, test-completion reports and residual-risk summaries. Provide objective recommendations while leaving formal acceptance and risk decisions with the client.<br><br>Minimum Requirements<br><br>Education<br><br>Bachelor's degree in information systems, computer science, software engineering or a related field. An equivalent combination of relevant education and directly applicable consulting or implementation experience may be considered.<br><br>Professional Experience<br><br>Typically 3-7 years in software, data or platform testing. Experience in software testing, data testing, quality assurance, platform testing or related delivery assurance. Experience testing data transformations, integrations, reports or analytical outputs. Experience managing defects, traceability, test evidence and user acceptance. Exposure to automated testing, non-functional testing or regulated delivery environments is preferred.<br><br>Technical and Domain Knowledge<br><br>Test strategy, planning, case design and traceability. Functional, integration, regression and user-acceptance testing. Data validation, reconciliation and quality-rule testing. API, pipeline, report, dashboard and platform testing. Defect lifecycle, severity, evidence and closure controls. Performance, usability and selected security-testing concepts. SQL or analytical tools for independent result validation. Test automation principles and controlled test-data management.<br><br>Core Competencies<br><br>Test design. Data validation. API/integration testing. Defect management. Automation basics. Professional scepticism. Test discipline. Independence. User advocacy. Challenging ambiguous requirements and unsupported readiness claims. Communicating defects objectively and constructively. Producing clear test evidence and executive quality reporting. Working independently while collaborating with delivery teams. Facilitating triage and user-acceptance sessions. Maintaining traceability and disciplined version control. Supporting client acceptance without assuming approval authority.<br><br>Preferred Certifications<br><br>ISTQB Certified Tester Foundation Leveladvanced test certification preferred for senior roles<br><br>Focus areas<br><br>Test design Data validation API/integration testing<br><br>Ready to apply for this role?<br><br>Apply for Data & Digital Quality Assurance Consultant

About the role:<br><br>Responsible for the performance analysis (proactive and reactive), validation and reporting of AOCC operational data in order to support decision making for procedural and conceptual improvements. The job also enhances the monitoring of the AOCC personnel performance on OPS data handling and hard resources allocation actions, with the scope to achieve a deeper insight on the improvement capabilities. Furthermore, the job plays a key role on the transformation of the AOCC reporting scheme.<br>Key responsibilities<br><br>Provide technical expertise to the information system team in major application deployment by assisting in designing process to arrive at high performance and optimal operational solutions. Develop consolidate operational dashboards, analyze and report of hard resources allocation related data and trends to the management team based on AOCC actions (real time vs planning, historic, etc.) Reduce manual operational jobs by ensuring automation of as many operational procedures for monitoring and supporting the day of operation responsibilities of AOCC. Develop supporting material and perform training to raise the data driven approach to decision making. Produce reports and analysis on internal performance of the AOCC department and AOCC personnel against the set KPls and other performance metrics. Ensure that this information is timely, accurate and highlights areas of opportunity or risk. To proactively research of operational issues to determine a source of data discrepancy or a trend and identify solutions for prevention of future discrepancy. Analyse information using various statistical methods, highlight patterns and trends within the data suggesting conclusions. Support Line Manager by designing and presenting conclusions gained from analysing data using statistical tools. Develop statistical / supporting data as advised by the management through presentations, business cases and management information reports. Attend Daily/ Weekly/ Monthly meetings with managers to understand the business requirements. Meet with business to discuss operational projects briefing providing current and targeted data that will help the business to set the KPl's outlined by the management. Collaborate with other data analytics and reporting teams to improve overall operational reporting capability and identify opportunities for improvements using alternative data sources. Design; develop automated reporting using the available corporate applications. Capture, analyse and present the data. Provide guidance to the AOCC duty team on how to use applicable data & information management and reporting systems. Perform other department duties related to the position as directed by the Head of the Department.<br>About you:<br><br>Bachelor's Degree or Equivalent with Minimum 4 years of job-related experience. Experienced in Airport Operations. Experienced in the roles and concept of operations control Centres. Strong analytical and presentation skills Data Analysis. Data visualization Excellent knowledge of the Microsoft office suite. Excellent knowledge of Microsoft Power Bl. Knowledge on Airport Operations Systems (AOS). Knowledge on Airport Operational Database (AODB). Database Performance Tuning. Database Management. Software Development Fundamentals. Data Maintenance. Database Security. Process Improvement. System Administration

About the role:<br><br>Responsible for the performance analysis (proactive and reactive), validation and reporting of AOCC operational data in order to support decision making for procedural and conceptual improvements. The job also enhances the monitoring of the AOCC personnel performance on OPS data handling and hard resources allocation actions, with the scope to achieve a deeper insight on the improvement capabilities. Furthermore, the job plays a key role on the transformation of the AOCC reporting scheme.<br>Key responsibilities<br><br>Provide technical expertise to the information system team in major application deployment by assisting in designing process to arrive at high performance and optimal operational solutions. Develop consolidate operational dashboards, analyze and report of hard resources allocation related data and trends to the management team based on AOCC actions (real time vs planning, historic, etc.) Reduce manual operational jobs by ensuring automation of as many operational procedures for monitoring and supporting the day of operation responsibilities of AOCC. Develop supporting material and perform training to raise the data driven approach to decision making. Produce reports and analysis on internal performance of the AOCC department and AOCC personnel against the set KPls and other performance metrics. Ensure that this information is timely, accurate and highlights areas of opportunity or risk. To proactively research of operational issues to determine a source of data discrepancy or a trend and identify solutions for prevention of future discrepancy. Analyse information using various statistical methods, highlight patterns and trends within the data suggesting conclusions. Support Line Manager by designing and presenting conclusions gained from analysing data using statistical tools. Develop statistical / supporting data as advised by the management through presentations, business cases and management information reports. Attend Daily/ Weekly/ Monthly meetings with managers to understand the business requirements. Meet with business to discuss operational projects briefing providing current and targeted data that will help the business to set the KPl's outlined by the management. Collaborate with other data analytics and reporting teams to improve overall operational reporting capability and identify opportunities for improvements using alternative data sources. Design; develop automated reporting using the available corporate applications. Capture, analyse and present the data. Provide guidance to the AOCC duty team on how to use applicable data & information management and reporting systems. Perform other department duties related to the position as directed by the Head of the Department.<br>About you:<br><br>Bachelor's Degree or Equivalent with Minimum 4 years of job-related experience. Experienced in Airport Operations. Experienced in the roles and concept of operations control Centres. Strong analytical and presentation skills Data Analysis. Data visualization Excellent knowledge of the Microsoft office suite. Excellent knowledge of Microsoft Power Bl. Knowledge on Airport Operations Systems (AOS). Knowledge on Airport Operational Database (AODB). Database Performance Tuning. Database Management. Software Development Fundamentals. Data Maintenance. Database Security. Process Improvement. System Administration

Master Data Specialist<br>???? Location: Doha, Qatar<br>Company: Palomba General Trading LLC<br>Employment Type: Full-time, On-site<br>⸻<br>Compensation<br>QAR 20,000 – 30,000 per month<br>Performance Bonus<br>Private Medical Insurance<br>Annual Flight Ticket<br>Annual Leave according to company policy<br>Professional Development Program<br>Career Advancement Opportunities<br>⸻<br>About Us<br>Palomba General Trading LLC is an international trading company headquartered in the United Arab Emirates, supplying pharmaceutical ingredients, nutraceutical ingredients, botanical extracts, food ingredients, essential oils, natural fragrance solutions and specialty raw materials to customers across the Middle East, Europe and selected international markets.<br>To support our growing international operations, we are looking for a Master Data Specialist to ensure the accuracy, consistency and integrity of product and business data across our commercial and operational systems.<br>⸻<br>Key Responsibilities<br>* Create and maintain product master data within ERP systems.* Manage product codes, customer records and supplier master data.* Ensure data accuracy, consistency and completeness across all business systems.* Review and validate product specifications and commercial information.* Coordinate data updates with Sales, Procurement, Logistics and Regulatory teams.* Support new product introductions and product lifecycle activities.* Monitor data quality and resolve master data issues.* Prepare master data reports and performance indicators.* Contribute to continuous improvement of data management processes.* Maintain documentation related to master data governance.<br>⸻<br>Requirements<br>* Bachelor’s degree in Business Administration, Supply Chain, Information Systems or related field.* Previous experience in Master Data, ERP Administration, Supply Chain or Business Operations is preferred.* Strong analytical and organizational skills.* Excellent attention to detail.* Advanced Microsoft Excel skills.* Experience with ERP systems such as SAP, Microsoft Dynamics, Oracle or similar is considered an advantage.* Professional English required.<br>⸻<br>Preferred Experience<br>Experience in one or more of the following sectors is considered an advantage:<br>* Pharmaceutical Ingredients* Nutraceutical Ingredients* Food Ingredients* Botanical Extracts* Essential Oils* Specialty Chemicals<br>⸻<br>What We Offer<br>* Competitive international compensation package.* Annual performance bonus.* Private medical insurance.* Annual return flight ticket.* Professional development opportunities.* Dynamic international working environment.* Long-term career growth.<br>⸻<br>Application<br>Please submit:<br>* Updated CV* Current location* Earliest availability* Expected salary<br>⸻<br>Why Join Palomba General Trading?<br>Join an expanding international trading company serving the pharmaceutical, nutraceutical, food and specialty ingredient industries. You will play a key role in maintaining high-quality business data, supporting operational excellence and enabling efficient collaboration across commercial, regulatory, logistics and supply chain functions.<br>Palomba General Trading LLC is an equal opportunity employer. All qualified applicants will be considered regardless of gender, age, nationality, ethnicity, religion or disability.

Master Data Specialist<br>???? Location: Doha, Qatar<br>Company: Palomba General Trading LLC<br>Employment Type: Full-time, On-site<br>⸻<br>Compensation<br>QAR 20,000 – 30,000 per month<br>Performance Bonus<br>Private Medical Insurance<br>Annual Flight Ticket<br>Annual Leave according to company policy<br>Professional Development Program<br>Career Advancement Opportunities<br>⸻<br>About Us<br>Palomba General Trading LLC is an international trading company headquartered in the United Arab Emirates, supplying pharmaceutical ingredients, nutraceutical ingredients, botanical extracts, food ingredients, essential oils, natural fragrance solutions and specialty raw materials to customers across the Middle East, Europe and selected international markets.<br>To support our growing international operations, we are looking for a Master Data Specialist to ensure the accuracy, consistency and integrity of product and business data across our commercial and operational systems.<br>⸻<br>Key Responsibilities<br>* Create and maintain product master data within ERP systems.* Manage product codes, customer records and supplier master data.* Ensure data accuracy, consistency and completeness across all business systems.* Review and validate product specifications and commercial information.* Coordinate data updates with Sales, Procurement, Logistics and Regulatory teams.* Support new product introductions and product lifecycle activities.* Monitor data quality and resolve master data issues.* Prepare master data reports and performance indicators.* Contribute to continuous improvement of data management processes.* Maintain documentation related to master data governance.<br>⸻<br>Requirements<br>* Bachelor’s degree in Business Administration, Supply Chain, Information Systems or related field.* Previous experience in Master Data, ERP Administration, Supply Chain or Business Operations is preferred.* Strong analytical and organizational skills.* Excellent attention to detail.* Advanced Microsoft Excel skills.* Experience with ERP systems such as SAP, Microsoft Dynamics, Oracle or similar is considered an advantage.* Professional English required.<br>⸻<br>Preferred Experience<br>Experience in one or more of the following sectors is considered an advantage:<br>* Pharmaceutical Ingredients* Nutraceutical Ingredients* Food Ingredients* Botanical Extracts* Essential Oils* Specialty Chemicals<br>⸻<br>What We Offer<br>* Competitive international compensation package.* Annual performance bonus.* Private medical insurance.* Annual return flight ticket.* Professional development opportunities.* Dynamic international working environment.* Long-term career growth.<br>⸻<br>Application<br>Please submit:<br>* Updated CV* Current location* Earliest availability* Expected salary<br>⸻<br>Why Join Palomba General Trading?<br>Join an expanding international trading company serving the pharmaceutical, nutraceutical, food and specialty ingredient industries. You will play a key role in maintaining high-quality business data, supporting operational excellence and enabling efficient collaboration across commercial, regulatory, logistics and supply chain functions.<br>Palomba General Trading LLC is an equal opportunity employer. All qualified applicants will be considered regardless of gender, age, nationality, ethnicity, religion or disability.

Master Data Specialist<br>???? Location: Doha, Qatar<br>Company: Palomba General Trading LLC<br>Employment Type: Full-time, On-site<br>⸻<br>Compensation<br>QAR 20,000 – 30,000 per month<br>Performance Bonus<br>Private Medical Insurance<br>Annual Flight Ticket<br>Annual Leave according to company policy<br>Professional Development Program<br>Career Advancement Opportunities<br>⸻<br>About Us<br>Palomba General Trading LLC is an international trading company headquartered in the United Arab Emirates, supplying pharmaceutical ingredients, nutraceutical ingredients, botanical extracts, food ingredients, essential oils, natural fragrance solutions and specialty raw materials to customers across the Middle East, Europe and selected international markets.<br>To support our growing international operations, we are looking for a Master Data Specialist to ensure the accuracy, consistency and integrity of product and business data across our commercial and operational systems.<br>⸻<br>Key Responsibilities<br>* Create and maintain product master data within ERP systems.* Manage product codes, customer records and supplier master data.* Ensure data accuracy, consistency and completeness across all business systems.* Review and validate product specifications and commercial information.* Coordinate data updates with Sales, Procurement, Logistics and Regulatory teams.* Support new product introductions and product lifecycle activities.* Monitor data quality and resolve master data issues.* Prepare master data reports and performance indicators.* Contribute to continuous improvement of data management processes.* Maintain documentation related to master data governance.<br>⸻<br>Requirements<br>* Bachelor’s degree in Business Administration, Supply Chain, Information Systems or related field.* Previous experience in Master Data, ERP Administration, Supply Chain or Business Operations is preferred.* Strong analytical and organizational skills.* Excellent attention to detail.* Advanced Microsoft Excel skills.* Experience with ERP systems such as SAP, Microsoft Dynamics, Oracle or similar is considered an advantage.* Professional English required.<br>⸻<br>Preferred Experience<br>Experience in one or more of the following sectors is considered an advantage:<br>* Pharmaceutical Ingredients* Nutraceutical Ingredients* Food Ingredients* Botanical Extracts* Essential Oils* Specialty Chemicals<br>⸻<br>What We Offer<br>* Competitive international compensation package.* Annual performance bonus.* Private medical insurance.* Annual return flight ticket.* Professional development opportunities.* Dynamic international working environment.* Long-term career growth.<br>⸻<br>Application<br>Please submit:<br>* Updated CV* Current location* Earliest availability* Expected salary<br>⸻<br>Why Join Palomba General Trading?<br>Join an expanding international trading company serving the pharmaceutical, nutraceutical, food and specialty ingredient industries. You will play a key role in maintaining high-quality business data, supporting operational excellence and enabling efficient collaboration across commercial, regulatory, logistics and supply chain functions.<br>Palomba General Trading LLC is an equal opportunity employer. All qualified applicants will be considered regardless of gender, age, nationality, ethnicity, religion or disability.

About QNB<br><br>Established in 1964 as the country’s first Qatari-owned commercial bank, QNB Group has steadily grown to become the largest bank in the Middle East and Africa (MEA) region.<br><br>QNB Group’s presence through its subsidiaries and associate companies extends to more than 31 countries across three continents providing a comprehensive range of advanced products and services. The total number of employees is more than 28,000 serving up to 20 million customers operating through 1,000 locations, with an ATM network of 4,300 machines.<br><br>QNB has maintained its position as one of the highest rated regional banks from leading credit rating agencies including Standard & Poor’s (A), Moody’s (Aa3) and Fitch (A+). The Bank has also been the recipient of many awards from leading international specialised financial publications.<br><br>Based on the Group’s consistent strong financial performance and its expanding international presence, QNB currently ranks as the most valuable bank brand in the Middle East and Africa, according to Brand Finance Magazine.<br><br>QNB Group has an active community support program and sponsors various social, educational and sporting events.<br><br>Job Summary<br><br>The data scientist plays a crucial role in driving advanced analytics and AI initiatives across the bank. This role collaborates closely with business and operational leaders to provide expert support, leveraging data analytical and AI tools to deliver strategic insights and actionable recommendations. Through hypothesis-based analysis to machine learning (ML) projects and applying Large Language Models, the data scientist models complex business problems using a variety of techniques including Predictive or prescriptive analytics, deep learning, Gen AI and visualization. Additionally, they support senior leadership by overseeing the development of business insights, reports, and AI capabilities to inform decision-making processes and drive impactful outcomes.<br><br>Main Responsibilities<br><br> Shareholder & Financial: - Implement Key Performance Indicators (KPIs) and monitor the performance of Data & AI-driven solutions to measure their impact on business outcomes. - Promote cost consciousness and efficiency in Data Analytics and AI projects to minimize expenses and maximize returns. - Implement Key Risk Indicators (KRIs) and manage the Group’s exposure to Data & AI related risk effectively accordingly. - Coordinate and obtain approval from the EVP Data & Analytics for projects and new systems that would impact capital or operating expenditures. - Take part in the overall QNB Data & Analytics strategy execution. - Communicate comprehensive and cost-effective Data, Analytics & AI solutions to user requirements keeping in mind the Group’s budgets and targets while enhancing productivity, to minimise cost, avoid waste, and optimise benefits for the bank. - Promote cost consciousness and efficiency and enhance productivity, to minimise cost, avoid waste, and optimise benefits for the bank. - Act within the limits of the powers delegated to the incumbent. Customer (Internal & External): - Collaborate closely with peers, key divisional stakeholders, and third-party support teams to identify and implement advanced data-driven and AI solutions that deliver substantial value for QNB and its customers. - Translate complex business needs into comprehensive data science and analytics requirements to support strategic business decision-making. - Provide strategic guidance regarding the potential and implementation of AI and data science within the organization. - Assist customers with thorough and insightful responses to their inquiries about the Bank’s products and strive to provide innovative solutions to their requests. - Ensure activities are conducted in accordance with Service Level Agreements (SLAs) with internal departments and units to achieve significant improvements in turnaround times. - Build and maintain robust and effective relationships with related departments and units to achieve the Group’s overarching objectives. - Provide precise and timely data to external and internal auditors, compliance teams, financial control, and risk management when required. - To assist customers in all their queries on Bank’s product and seek solution to their requests. - Maintain activities in accordance with Service Level Agreements (SLAs) with internal departments/units to achieve improvements in turn-around time. - Build and maintain strong/effective relationships with related departments/units to achieve the Group’s objectives. - Provide timely/accurate data to external/internal Auditors, Compliance, Financial Control and Risk when required. Internal (Processes, Products, Regulatory): Develop predictive models using a variety of advanced machine learning techniques to extract meaningful insights. - Research and implement cutting-edge techniques and tools in data analytics and artificial intelligence to streamline data analysis processes and enhance decision-making. - Identify and implement new statistical or mathematical methodologies as required for specific data-driven projects. - Build robust data-driven models to address complex business questions and employ large-scale experimentation, analysis, and visualization techniques to generate efficient and repeatable insights. - Integrate domain knowledge into AI solutions, such as leveraging financial risk data, customer journey analytics, quality predictions, and sales and marketing data. - Continuously monitor the performance and health of AI-driven models, ensuring high-quality outputs and efficiency. - Establish best practices for AI development and production infrastructure, including cloud computing, Spark, GPU utilization, and containerization. - Design and conduct analytics with the highest standards of model validation, accuracy, encompassing study design, methodology, algorithms, and statistical modelling. Learning & Knowledge: - Ensure a comprehensive understanding of business requirements to deliver the most effective data, analytics, and AI solutions. - Possess detailed knowledge of system architecture and limitations to determine optimal problem-solving methods. - Understand user requirements and existing data structures to provide appropriate solutions by enhancing existing systems or implementing new ones. - Stay updated with methodologies, tools, and industry trends in machine learning, artificial intelligence, and data analytics. - Proactively identify areas for professional development in data science and undertake relevant development activities. - Seek out opportunities to stay current with advancements in AI and data analytics fields. - Initiate regular meetings within the Application Development department focused on discussing progress, resolving issues, and addressing concerns related to AI and data analytics projects. Legal, Regulatory, and Risk Framework Responsibilities: - Adhere to all pertinent legal, regulatory, and internal compliance requirements, including but not limited to policies on Data Protection, Fraud Control, and Anti-Money Laundering (AML) & Counter-Terrorist Financing (CTF). - Understand and effectively perform your role within the Three Lines of Defence framework to identify, measure, monitor, manage, and report risks related to data, analytics, and AI projects. - Ensure optimal outcomes for clients in line with Conduct Risk policy by leveraging AI and analytics tools ethically and responsibly. - Support the Risk and Control Self-Assessment (RCSA), Key Risk Indicators (KRI), incident reporting, and remediation processes, as applicable, in accordance with Operational Risk Management guidelines specific to data and AI initiatives. - Complete all mandatory training provided by the organization to achieve and maintain the required levels of competence in data science, analytics, and AI fields. - Attend all required (internal and external) seminars and workshops, as instructed, to stay abreast of the latest advancements and best practices in data analytics and AI. Other: - Ensure high standards of data protection and confidentiality to safeguard all data and systems. - Maintaining utmost confidentiality concerning customer data and internal information obtained during the course of business and provide such information on a need-to-know basis only to Senior Management, Audit and Compliance functions, and relevant Regulators. - Maintain high professional standards to uphold the organization's reputation and to strengthen its leadership position in data analytics and AI. - All other ad hoc duties/activities related to data analytics and AI that management might request from time to time<br><br>Education And Experience Requirements<br><br> University graduate preferably with a Major in computer science, data science, software engineering, information systems, or a related quantitative field. At least 10 years of relevant experience, preferably within a Data Scientist or related role. A PhD in statistics, ML, computer science or the natural sciences, especially physics or any engineering disciplines or equivalent, would be desirable. Candidates must have a specialization in ML, AI, cognitive science, or data science, with extensive hands-on experience in developing data science and AI solutions using machine learning, deep learning, and LLM techniques. Sound knowledge and implementation experience on LLM based solutions. Prior experience in banking is desirable Sound knowledge in cloud technologies ,Python and full stack engineering is must.<br><br>Note: you will be required to attach the following:<br><br>Resume/CVCopy of Passport or QID Copy of Education Certificate

About QNB<br><br>Established in 1964 as the country’s first Qatari-owned commercial bank, QNB Group has steadily grown to become the largest bank in the Middle East and Africa (MEA) region.<br><br>QNB Group’s presence through its subsidiaries and associate companies extends to more than 31 countries across three continents providing a comprehensive range of advanced products and services. The total number of employees is more than 28,000 serving up to 20 million customers operating through 1,000 locations, with an ATM network of 4,300 machines.<br><br>QNB has maintained its position as one of the highest rated regional banks from leading credit rating agencies including Standard & Poor’s (A), Moody’s (Aa3) and Fitch (A+). The Bank has also been the recipient of many awards from leading international specialised financial publications.<br><br>Based on the Group’s consistent strong financial performance and its expanding international presence, QNB currently ranks as the most valuable bank brand in the Middle East and Africa, according to Brand Finance Magazine.<br><br>QNB Group has an active community support program and sponsors various social, educational and sporting events.<br><br>Job Summary<br><br>The data scientist plays a crucial role in driving advanced analytics and AI initiatives across the bank. This role collaborates closely with business and operational leaders to provide expert support, leveraging data analytical and AI tools to deliver strategic insights and actionable recommendations. Through hypothesis-based analysis to machine learning (ML) projects and applying Large Language Models, the data scientist models complex business problems using a variety of techniques including Predictive or prescriptive analytics, deep learning, Gen AI and visualization. Additionally, they support senior leadership by overseeing the development of business insights, reports, and AI capabilities to inform decision-making processes and drive impactful outcomes.<br><br>Main Responsibilities<br><br> Shareholder & Financial: - Implement Key Performance Indicators (KPIs) and monitor the performance of Data & AI-driven solutions to measure their impact on business outcomes. - Promote cost consciousness and efficiency in Data Analytics and AI projects to minimize expenses and maximize returns. - Implement Key Risk Indicators (KRIs) and manage the Group’s exposure to Data & AI related risk effectively accordingly. - Coordinate and obtain approval from the EVP Data & Analytics for projects and new systems that would impact capital or operating expenditures. - Take part in the overall QNB Data & Analytics strategy execution. - Communicate comprehensive and cost-effective Data, Analytics & AI solutions to user requirements keeping in mind the Group’s budgets and targets while enhancing productivity, to minimise cost, avoid waste, and optimise benefits for the bank. - Promote cost consciousness and efficiency and enhance productivity, to minimise cost, avoid waste, and optimise benefits for the bank. - Act within the limits of the powers delegated to the incumbent. Customer (Internal & External): - Collaborate closely with peers, key divisional stakeholders, and third-party support teams to identify and implement advanced data-driven and AI solutions that deliver substantial value for QNB and its customers. - Translate complex business needs into comprehensive data science and analytics requirements to support strategic business decision-making. - Provide strategic guidance regarding the potential and implementation of AI and data science within the organization. - Assist customers with thorough and insightful responses to their inquiries about the Bank’s products and strive to provide innovative solutions to their requests. - Ensure activities are conducted in accordance with Service Level Agreements (SLAs) with internal departments and units to achieve significant improvements in turnaround times. - Build and maintain robust and effective relationships with related departments and units to achieve the Group’s overarching objectives. - Provide precise and timely data to external and internal auditors, compliance teams, financial control, and risk management when required. - To assist customers in all their queries on Bank’s product and seek solution to their requests. - Maintain activities in accordance with Service Level Agreements (SLAs) with internal departments/units to achieve improvements in turn-around time. - Build and maintain strong/effective relationships with related departments/units to achieve the Group’s objectives. - Provide timely/accurate data to external/internal Auditors, Compliance, Financial Control and Risk when required. Internal (Processes, Products, Regulatory): Develop predictive models using a variety of advanced machine learning techniques to extract meaningful insights. - Research and implement cutting-edge techniques and tools in data analytics and artificial intelligence to streamline data analysis processes and enhance decision-making. - Identify and implement new statistical or mathematical methodologies as required for specific data-driven projects. - Build robust data-driven models to address complex business questions and employ large-scale experimentation, analysis, and visualization techniques to generate efficient and repeatable insights. - Integrate domain knowledge into AI solutions, such as leveraging financial risk data, customer journey analytics, quality predictions, and sales and marketing data. - Continuously monitor the performance and health of AI-driven models, ensuring high-quality outputs and efficiency. - Establish best practices for AI development and production infrastructure, including cloud computing, Spark, GPU utilization, and containerization. - Design and conduct analytics with the highest standards of model validation, accuracy, encompassing study design, methodology, algorithms, and statistical modelling. Learning & Knowledge: - Ensure a comprehensive understanding of business requirements to deliver the most effective data, analytics, and AI solutions. - Possess detailed knowledge of system architecture and limitations to determine optimal problem-solving methods. - Understand user requirements and existing data structures to provide appropriate solutions by enhancing existing systems or implementing new ones. - Stay updated with methodologies, tools, and industry trends in machine learning, artificial intelligence, and data analytics. - Proactively identify areas for professional development in data science and undertake relevant development activities. - Seek out opportunities to stay current with advancements in AI and data analytics fields. - Initiate regular meetings within the Application Development department focused on discussing progress, resolving issues, and addressing concerns related to AI and data analytics projects. Legal, Regulatory, and Risk Framework Responsibilities: - Adhere to all pertinent legal, regulatory, and internal compliance requirements, including but not limited to policies on Data Protection, Fraud Control, and Anti-Money Laundering (AML) & Counter-Terrorist Financing (CTF). - Understand and effectively perform your role within the Three Lines of Defence framework to identify, measure, monitor, manage, and report risks related to data, analytics, and AI projects. - Ensure optimal outcomes for clients in line with Conduct Risk policy by leveraging AI and analytics tools ethically and responsibly. - Support the Risk and Control Self-Assessment (RCSA), Key Risk Indicators (KRI), incident reporting, and remediation processes, as applicable, in accordance with Operational Risk Management guidelines specific to data and AI initiatives. - Complete all mandatory training provided by the organization to achieve and maintain the required levels of competence in data science, analytics, and AI fields. - Attend all required (internal and external) seminars and workshops, as instructed, to stay abreast of the latest advancements and best practices in data analytics and AI. Other: - Ensure high standards of data protection and confidentiality to safeguard all data and systems. - Maintaining utmost confidentiality concerning customer data and internal information obtained during the course of business and provide such information on a need-to-know basis only to Senior Management, Audit and Compliance functions, and relevant Regulators. - Maintain high professional standards to uphold the organization's reputation and to strengthen its leadership position in data analytics and AI. - All other ad hoc duties/activities related to data analytics and AI that management might request from time to time<br><br>Education And Experience Requirements<br><br> University graduate preferably with a Major in computer science, data science, software engineering, information systems, or a related quantitative field. At least 10 years of relevant experience, preferably within a Data Scientist or related role. A PhD in statistics, ML, computer science or the natural sciences, especially physics or any engineering disciplines or equivalent, would be desirable. Candidates must have a specialization in ML, AI, cognitive science, or data science, with extensive hands-on experience in developing data science and AI solutions using machine learning, deep learning, and LLM techniques. Sound knowledge and implementation experience on LLM based solutions. Prior experience in banking is desirable Sound knowledge in cloud technologies ,Python and full stack engineering is must.<br><br>Note: you will be required to attach the following:<br><br>Resume/CVCopy of Passport or QID Copy of Education Certificate

About QNB<br><br>Established in 1964 as the country’s first Qatari-owned commercial bank, QNB Group has steadily grown to become the largest bank in the Middle East and Africa (MEA) region.<br><br>QNB Group’s presence through its subsidiaries and associate companies extends to more than 31 countries across three continents providing a comprehensive range of advanced products and services. The total number of employees is more than 28,000 serving up to 20 million customers operating through 1,000 locations, with an ATM network of 4,300 machines.<br><br>QNB has maintained its position as one of the highest rated regional banks from leading credit rating agencies including Standard & Poor’s (A), Moody’s (Aa3) and Fitch (A+). The Bank has also been the recipient of many awards from leading international specialised financial publications.<br><br>Based on the Group’s consistent strong financial performance and its expanding international presence, QNB currently ranks as the most valuable bank brand in the Middle East and Africa, according to Brand Finance Magazine.<br><br>QNB Group has an active community support program and sponsors various social, educational and sporting events.<br><br>Job Summary<br><br>The data scientist plays a crucial role in driving advanced analytics and AI initiatives across the bank. This role collaborates closely with business and operational leaders to provide expert support, leveraging data analytical and AI tools to deliver strategic insights and actionable recommendations. Through hypothesis-based analysis to machine learning (ML) projects and applying Large Language Models, the data scientist models complex business problems using a variety of techniques including Predictive or prescriptive analytics, deep learning, Gen AI and visualization. Additionally, they support senior leadership by overseeing the development of business insights, reports, and AI capabilities to inform decision-making processes and drive impactful outcomes.<br><br>Main Responsibilities<br><br> Shareholder & Financial: - Implement Key Performance Indicators (KPIs) and monitor the performance of Data & AI-driven solutions to measure their impact on business outcomes. - Promote cost consciousness and efficiency in Data Analytics and AI projects to minimize expenses and maximize returns. - Implement Key Risk Indicators (KRIs) and manage the Group’s exposure to Data & AI related risk effectively accordingly. - Coordinate and obtain approval from the EVP Data & Analytics for projects and new systems that would impact capital or operating expenditures. - Take part in the overall QNB Data & Analytics strategy execution. - Communicate comprehensive and cost-effective Data, Analytics & AI solutions to user requirements keeping in mind the Group’s budgets and targets while enhancing productivity, to minimise cost, avoid waste, and optimise benefits for the bank. - Promote cost consciousness and efficiency and enhance productivity, to minimise cost, avoid waste, and optimise benefits for the bank. - Act within the limits of the powers delegated to the incumbent. Customer (Internal & External): - Collaborate closely with peers, key divisional stakeholders, and third-party support teams to identify and implement advanced data-driven and AI solutions that deliver substantial value for QNB and its customers. - Translate complex business needs into comprehensive data science and analytics requirements to support strategic business decision-making. - Provide strategic guidance regarding the potential and implementation of AI and data science within the organization. - Assist customers with thorough and insightful responses to their inquiries about the Bank’s products and strive to provide innovative solutions to their requests. - Ensure activities are conducted in accordance with Service Level Agreements (SLAs) with internal departments and units to achieve significant improvements in turnaround times. - Build and maintain robust and effective relationships with related departments and units to achieve the Group’s overarching objectives. - Provide precise and timely data to external and internal auditors, compliance teams, financial control, and risk management when required. - To assist customers in all their queries on Bank’s product and seek solution to their requests. - Maintain activities in accordance with Service Level Agreements (SLAs) with internal departments/units to achieve improvements in turn-around time. - Build and maintain strong/effective relationships with related departments/units to achieve the Group’s objectives. - Provide timely/accurate data to external/internal Auditors, Compliance, Financial Control and Risk when required. Internal (Processes, Products, Regulatory): Develop predictive models using a variety of advanced machine learning techniques to extract meaningful insights. - Research and implement cutting-edge techniques and tools in data analytics and artificial intelligence to streamline data analysis processes and enhance decision-making. - Identify and implement new statistical or mathematical methodologies as required for specific data-driven projects. - Build robust data-driven models to address complex business questions and employ large-scale experimentation, analysis, and visualization techniques to generate efficient and repeatable insights. - Integrate domain knowledge into AI solutions, such as leveraging financial risk data, customer journey analytics, quality predictions, and sales and marketing data. - Continuously monitor the performance and health of AI-driven models, ensuring high-quality outputs and efficiency. - Establish best practices for AI development and production infrastructure, including cloud computing, Spark, GPU utilization, and containerization. - Design and conduct analytics with the highest standards of model validation, accuracy, encompassing study design, methodology, algorithms, and statistical modelling. Learning & Knowledge: - Ensure a comprehensive understanding of business requirements to deliver the most effective data, analytics, and AI solutions. - Possess detailed knowledge of system architecture and limitations to determine optimal problem-solving methods. - Understand user requirements and existing data structures to provide appropriate solutions by enhancing existing systems or implementing new ones. - Stay updated with methodologies, tools, and industry trends in machine learning, artificial intelligence, and data analytics. - Proactively identify areas for professional development in data science and undertake relevant development activities. - Seek out opportunities to stay current with advancements in AI and data analytics fields. - Initiate regular meetings within the Application Development department focused on discussing progress, resolving issues, and addressing concerns related to AI and data analytics projects. Legal, Regulatory, and Risk Framework Responsibilities: - Adhere to all pertinent legal, regulatory, and internal compliance requirements, including but not limited to policies on Data Protection, Fraud Control, and Anti-Money Laundering (AML) & Counter-Terrorist Financing (CTF). - Understand and effectively perform your role within the Three Lines of Defence framework to identify, measure, monitor, manage, and report risks related to data, analytics, and AI projects. - Ensure optimal outcomes for clients in line with Conduct Risk policy by leveraging AI and analytics tools ethically and responsibly. - Support the Risk and Control Self-Assessment (RCSA), Key Risk Indicators (KRI), incident reporting, and remediation processes, as applicable, in accordance with Operational Risk Management guidelines specific to data and AI initiatives. - Complete all mandatory training provided by the organization to achieve and maintain the required levels of competence in data science, analytics, and AI fields. - Attend all required (internal and external) seminars and workshops, as instructed, to stay abreast of the latest advancements and best practices in data analytics and AI. Other: - Ensure high standards of data protection and confidentiality to safeguard all data and systems. - Maintaining utmost confidentiality concerning customer data and internal information obtained during the course of business and provide such information on a need-to-know basis only to Senior Management, Audit and Compliance functions, and relevant Regulators. - Maintain high professional standards to uphold the organization's reputation and to strengthen its leadership position in data analytics and AI. - All other ad hoc duties/activities related to data analytics and AI that management might request from time to time<br><br>Education And Experience Requirements<br><br> University graduate preferably with a Major in computer science, data science, software engineering, information systems, or a related quantitative field. At least 10 years of relevant experience, preferably within a Data Scientist or related role. A PhD in statistics, ML, computer science or the natural sciences, especially physics or any engineering disciplines or equivalent, would be desirable. Candidates must have a specialization in ML, AI, cognitive science, or data science, with extensive hands-on experience in developing data science and AI solutions using machine learning, deep learning, and LLM techniques. Sound knowledge and implementation experience on LLM based solutions. Prior experience in banking is desirable Sound knowledge in cloud technologies ,Python and full stack engineering is must.<br><br>Note: you will be required to attach the following:<br><br>Resume/CVCopy of Passport or QID Copy of Education Certificate

About QNB<br><br>Established in 1964 as the country’s first Qatari-owned commercial bank, QNB Group has steadily grown to become the largest bank in the Middle East and Africa (MEA) region.<br><br>QNB Group’s presence through its subsidiaries and associate companies extends to more than 31 countries across three continents providing a comprehensive range of advanced products and services. The total number of employees is more than 28,000 serving up to 20 million customers operating through 1,000 locations, with an ATM network of 4,300 machines.<br><br>QNB has maintained its position as one of the highest rated regional banks from leading credit rating agencies including Standard & Poor’s (A), Moody’s (Aa3) and Fitch (A+). The Bank has also been the recipient of many awards from leading international specialised financial publications.<br><br>Based on the Group’s consistent strong financial performance and its expanding international presence, QNB currently ranks as the most valuable bank brand in the Middle East and Africa, according to Brand Finance Magazine.<br><br>QNB Group has an active community support program and sponsors various social, educational and sporting events.<br><br>Job Summary<br><br>The data scientist plays a crucial role in driving advanced analytics and AI initiatives across the bank. This role collaborates closely with business and operational leaders to provide expert support, leveraging data analytical and AI tools to deliver strategic insights and actionable recommendations. Through hypothesis-based analysis to machine learning (ML) projects and applying Large Language Models, the data scientist models complex business problems using a variety of techniques including Predictive or prescriptive analytics, deep learning, Gen AI and visualization. Additionally, they support senior leadership by overseeing the development of business insights, reports, and AI capabilities to inform decision-making processes and drive impactful outcomes.<br><br>Main Responsibilities<br><br> Shareholder & Financial: - Implement Key Performance Indicators (KPIs) and monitor the performance of Data & AI-driven solutions to measure their impact on business outcomes. - Promote cost consciousness and efficiency in Data Analytics and AI projects to minimize expenses and maximize returns. - Implement Key Risk Indicators (KRIs) and manage the Group’s exposure to Data & AI related risk effectively accordingly. - Coordinate and obtain approval from the EVP Data & Analytics for projects and new systems that would impact capital or operating expenditures. - Take part in the overall QNB Data & Analytics strategy execution. - Communicate comprehensive and cost-effective Data, Analytics & AI solutions to user requirements keeping in mind the Group’s budgets and targets while enhancing productivity, to minimise cost, avoid waste, and optimise benefits for the bank. - Promote cost consciousness and efficiency and enhance productivity, to minimise cost, avoid waste, and optimise benefits for the bank. - Act within the limits of the powers delegated to the incumbent. Customer (Internal & External): - Collaborate closely with peers, key divisional stakeholders, and third-party support teams to identify and implement advanced data-driven and AI solutions that deliver substantial value for QNB and its customers. - Translate complex business needs into comprehensive data science and analytics requirements to support strategic business decision-making. - Provide strategic guidance regarding the potential and implementation of AI and data science within the organization. - Assist customers with thorough and insightful responses to their inquiries about the Bank’s products and strive to provide innovative solutions to their requests. - Ensure activities are conducted in accordance with Service Level Agreements (SLAs) with internal departments and units to achieve significant improvements in turnaround times. - Build and maintain robust and effective relationships with related departments and units to achieve the Group’s overarching objectives. - Provide precise and timely data to external and internal auditors, compliance teams, financial control, and risk management when required. - To assist customers in all their queries on Bank’s product and seek solution to their requests. - Maintain activities in accordance with Service Level Agreements (SLAs) with internal departments/units to achieve improvements in turn-around time. - Build and maintain strong/effective relationships with related departments/units to achieve the Group’s objectives. - Provide timely/accurate data to external/internal Auditors, Compliance, Financial Control and Risk when required. Internal (Processes, Products, Regulatory): Develop predictive models using a variety of advanced machine learning techniques to extract meaningful insights. - Research and implement cutting-edge techniques and tools in data analytics and artificial intelligence to streamline data analysis processes and enhance decision-making. - Identify and implement new statistical or mathematical methodologies as required for specific data-driven projects. - Build robust data-driven models to address complex business questions and employ large-scale experimentation, analysis, and visualization techniques to generate efficient and repeatable insights. - Integrate domain knowledge into AI solutions, such as leveraging financial risk data, customer journey analytics, quality predictions, and sales and marketing data. - Continuously monitor the performance and health of AI-driven models, ensuring high-quality outputs and efficiency. - Establish best practices for AI development and production infrastructure, including cloud computing, Spark, GPU utilization, and containerization. - Design and conduct analytics with the highest standards of model validation, accuracy, encompassing study design, methodology, algorithms, and statistical modelling. Learning & Knowledge: - Ensure a comprehensive understanding of business requirements to deliver the most effective data, analytics, and AI solutions. - Possess detailed knowledge of system architecture and limitations to determine optimal problem-solving methods. - Understand user requirements and existing data structures to provide appropriate solutions by enhancing existing systems or implementing new ones. - Stay updated with methodologies, tools, and industry trends in machine learning, artificial intelligence, and data analytics. - Proactively identify areas for professional development in data science and undertake relevant development activities. - Seek out opportunities to stay current with advancements in AI and data analytics fields. - Initiate regular meetings within the Application Development department focused on discussing progress, resolving issues, and addressing concerns related to AI and data analytics projects. Legal, Regulatory, and Risk Framework Responsibilities: - Adhere to all pertinent legal, regulatory, and internal compliance requirements, including but not limited to policies on Data Protection, Fraud Control, and Anti-Money Laundering (AML) & Counter-Terrorist Financing (CTF). - Understand and effectively perform your role within the Three Lines of Defence framework to identify, measure, monitor, manage, and report risks related to data, analytics, and AI projects. - Ensure optimal outcomes for clients in line with Conduct Risk policy by leveraging AI and analytics tools ethically and responsibly. - Support the Risk and Control Self-Assessment (RCSA), Key Risk Indicators (KRI), incident reporting, and remediation processes, as applicable, in accordance with Operational Risk Management guidelines specific to data and AI initiatives. - Complete all mandatory training provided by the organization to achieve and maintain the required levels of competence in data science, analytics, and AI fields. - Attend all required (internal and external) seminars and workshops, as instructed, to stay abreast of the latest advancements and best practices in data analytics and AI. Other: - Ensure high standards of data protection and confidentiality to safeguard all data and systems. - Maintaining utmost confidentiality concerning customer data and internal information obtained during the course of business and provide such information on a need-to-know basis only to Senior Management, Audit and Compliance functions, and relevant Regulators. - Maintain high professional standards to uphold the organization's reputation and to strengthen its leadership position in data analytics and AI. - All other ad hoc duties/activities related to data analytics and AI that management might request from time to time<br><br>Education And Experience Requirements<br><br> University graduate preferably with a Major in computer science, data science, software engineering, information systems, or a related quantitative field. At least 10 years of relevant experience, preferably within a Data Scientist or related role. A PhD in statistics, ML, computer science or the natural sciences, especially physics or any engineering disciplines or equivalent, would be desirable. Candidates must have a specialization in ML, AI, cognitive science, or data science, with extensive hands-on experience in developing data science and AI solutions using machine learning, deep learning, and LLM techniques. Sound knowledge and implementation experience on LLM based solutions. Prior experience in banking is desirable Sound knowledge in cloud technologies ,Python and full stack engineering is must.<br><br>Note: you will be required to attach the following:<br><br>Resume/CVCopy of Passport or QID Copy of Education Certificate

At EY, we're all in to shape your future with confidence.<br><br>We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go.<br><br>Join EY and help to build a better working world.<br><br>Key Responsibilities<br><br> Understand ongoing business problems and translate them into research and analytical studies Identify relevant data sources and define the type of data required for analysis Gather, clean, and prepare data for analysis to ensure accuracy and reliability Perform in-depth data analysis to extract meaningful insights Interpret findings and present actionable recommendations to support decision-making<br><br>Experience, Professional Qualifications & Criteria<br><br> Degree in relevant fields such as Statistics, Mathematics, Economics, or a related analytical discipline 10+ years of Proven experience in data analytics or a similar analytical role Professional Certification (preferred): Data Analytics Professional Certificate<br><br>Language Requirements<br><br> Fluency in Arabic (mandatory) Strong proficiency in English<br><br>Technical Skills<br><br> Strong mathematical and analytical skills for collecting, measuring, organizing, and analyzing data Working knowledge of programming languages such as SQL, Python, R, and Oracle Experience with data models, database design development, segmentation, and data mining techniques Hands-on experience with reporting tools, databases, and frameworks (XML, ETL, Java Script frameworks) In-depth understanding of statistical methods and tools used to analyze datasets Familiarity with big data platforms such as Apache Spark and Hadoop Proficiency in data visualization tools including Power BI and Tableau Ability to design and apply algorithms to derive insights and solutions from datasets<br><br>Soft Skills<br><br> Strong critical thinking and analytical capabilities Excellent communication and presentation skills Problem-solving mindset with attention to detail Ability to manage multiple priorities effectively<br><br>Team Skills<br><br> Strong collaboration and teamwork abilities Creativity and structured thinking Solid experience in report writing, presentations, and data querying Excellent written and verbal communication skills Understanding of industry-specific data analysis practices<br><br>At EY, we'll develop you with future-focused skills and equip you with world-class experiences. We'll empower you in a flexible environment and fuel your extraordinary talents in a diverse and inclusive culture of globally connected teams.<br><br>Are you ready to shape your future with confidence? Apply today.<br><br>To help create the best experience during the recruitment process, please describe any disability-related adjustments or accommodations you may need.<br><br>EY | Building a better working world<br><br>EY is building a better working world by creating new value for clients, people, society, and the planet, while building trust in capital markets.<br><br>Enabled by data, AI, and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.<br><br>EY teams work across a full spectrum of services in assurance, consulting, tax, strategy, and transactions, supporting clients in more than 150 countries and territories.

Role Purpose<br><br>The Data Governance Consultant helps clients design, document and activate practical governance arrangements for their data. The role works with business, data, technology, security and compliance stakeholders to clarify decision rights, establish ownership and stewardship, develop policies and operating procedures, and create the registers and reporting mechanisms needed to sustain governance.<br><br>The consultant combines structured analysis with facilitation and high-quality documentation. Work may include evidence reviews, maturity assessments, role mapping, committee support, policy drafting, issue tracking and governance-performance reporting. The consultant prepares options and recommendations for client approval and supports implementation, but does not become the client's Data Owner, policy owner or governance authority. The expected outcome is a set of usable governance practices and artefacts that client teams understand and can operate after handover.<br><br>Key Responsibilities<br><br>Conduct governance discovery interviews and review policies, charters, role descriptions, registers, reports and implementation evidence. Support data-management maturity and governance-capability assessments using traceable evidence. Draft governance frameworks, operating procedures, policies, standards, charters and decision records. Map client roles and responsibilities and develop practical RACI matrices for governance activities. Support the definition of Data Owner, Data Steward, focal-point, committee and working-group practices. Prepare workshop materials and facilitate discussions on mandates, ownership, escalation and policy requirements. Maintain issue, decision, action, exception and dependency registers for governance workstreams. Prepare committee agendas, evidence summaries, recommendations and follow-up records without exercising client approval rights. Develop governance indicators and reporting views that show adoption, issues, decisions and implementation progress. Coordinate governance requirements with metadata, quality, architecture, sharing, security, content and analytics teams. Support policy communication, role-based training and governance activation across client departments. Document implementation decisions and transfer tools, methods and operating guidance to client personnel.<br><br>Minimum Requirements<br><br>Education<br><br>Bachelor's degree in information systems, data management, business, public administration or a related field. An equivalent combination of relevant education and directly applicable consulting or implementation experience may be considered.<br><br>Professional Experience<br><br>Typically 4-8 years in data governance, information governance, risk, compliance or data management. Experience supporting data-governance, information-governance, risk, compliance or data-management initiatives. Practical experience drafting policies, procedures, RACI matrices, charters, registers or governance reports. Experience engaging business and technical stakeholders and documenting agreed decisions. Exposure to public-sector or regulated environments is preferred.<br><br>Technical and Domain Knowledge<br><br>Data-governance principles, operating models and decision rights. Policy and standards lifecycle, exceptions and compliance evidence. Data ownership, stewardship and committee practices. Governance maturity assessment and evidence mapping. Issue, action, decision and risk registers. Governance indicators, reporting and implementation tracking. Interfaces with metadata, data quality, architecture, sharing and security. Working knowledge of QDKC-aligned governance artefacts and processes.<br><br>Core Competencies<br><br>Governance frameworks. Policy drafting. RACI design. Issue management. Documentation and reporting. Documentation discipline. Stakeholder coordination. Structured interviewing and evidence collection. Workshop preparation, facilitation and accurate decision capture. Clear policy, procedure and report writing. Translating governance concepts into practical business actions. Managing stakeholders with different mandates and priorities. Producing traceable deliverables and maintaining version control. Supporting implementation while respecting client accountability.<br><br>Preferred Certifications<br><br>CDMP Associate or Practitioner, with Data Governance specialty preferred Prosci Change Practitioner<br><br>Focus areas<br><br>Governance frameworks Policy drafting Facilitation<br><br>Ready to apply for this role?<br><br>Apply for Data Governance Consultant

Job Summary<br>We are seeking a detail-oriented and analytical Data Analyst with experience in a contact centre environment and strong Workforce Management (WFM) capabilities. The ideal candidate will be responsible for analysing operational data, optimizing workforce planning, and delivering actionable insights to improve performance, efficiency, and customer experience.<br><br>Key Responsibilities<br>Data Analysis & Reporting Analyze large datasets to identify trends, patterns, and insights related to contact centre performance. Develop and maintain dashboards and reports using tools such as Power BI or Tableau. Provide daily, weekly, and monthly performance reports (KPIs, SLAs, service levels, etc.). Support data-driven decision-making through accurate and timely analysis. Workforce Management (WFM) Perform forecasting of call volumes, workload, and staffing requirements. Develop and manage scheduling plans to ensure optimal resource utilization. Conduct real-time monitoring (RTA) of contact center operations and recommend adjustments. Analyze shrinkage, occupancy, and adherence metrics to improve efficiency. Process Improvement Identify operational inefficiencies and recommend process improvements. Collaborate with operations and team leaders to enhance productivity and service delivery. Support continuous improvement initiatives through data insights. Data Management Extract, clean, and manipulate data using SQL and Excel. Ensure data accuracy, integrity, and consistency across reports. Automate reporting processes where possible.<br><br>Required Skills & Qualifications<br>Bachelor’s degree in Data Analytics, Statistics, Mathematics, Business, or related field. Minimum 2 years of experience in data analysis within a contact center environment. Strong Workforce Management (WFM) experience (forecasting, scheduling, real-time monitoring). Advanced proficiency in Microsoft Excel (Pivot Tables, VLOOKUP, Macros preferred). Strong knowledge of SQL for data extraction and manipulation. Experience with reporting and visualization tools such as Power BI or Tableau. Solid understanding of contact center metrics (AHT, SLA, Service Level, Occupancy, etc.). Strong analytical, problem-solving, and communication skills.<br><br>Preferred Qualifications<br>Experience with WFM tools (e.g., NICE, Verint, Aspect, Genesys). Knowledge of automation tools or scripting (Python is a plus). Experience working in a high-volume customer service environment.

Job Summary<br>We are seeking a detail-oriented and analytical Data Analyst with experience in a contact centre environment and strong Workforce Management (WFM) capabilities. The ideal candidate will be responsible for analysing operational data, optimizing workforce planning, and delivering actionable insights to improve performance, efficiency, and customer experience.<br><br>Key Responsibilities<br>Data Analysis & Reporting Analyze large datasets to identify trends, patterns, and insights related to contact centre performance. Develop and maintain dashboards and reports using tools such as Power BI or Tableau. Provide daily, weekly, and monthly performance reports (KPIs, SLAs, service levels, etc.). Support data-driven decision-making through accurate and timely analysis. Workforce Management (WFM) Perform forecasting of call volumes, workload, and staffing requirements. Develop and manage scheduling plans to ensure optimal resource utilization. Conduct real-time monitoring (RTA) of contact center operations and recommend adjustments. Analyze shrinkage, occupancy, and adherence metrics to improve efficiency. Process Improvement Identify operational inefficiencies and recommend process improvements. Collaborate with operations and team leaders to enhance productivity and service delivery. Support continuous improvement initiatives through data insights. Data Management Extract, clean, and manipulate data using SQL and Excel. Ensure data accuracy, integrity, and consistency across reports. Automate reporting processes where possible.<br><br>Required Skills & Qualifications<br>Bachelor’s degree in Data Analytics, Statistics, Mathematics, Business, or related field. Minimum 2 years of experience in data analysis within a contact center environment. Strong Workforce Management (WFM) experience (forecasting, scheduling, real-time monitoring). Advanced proficiency in Microsoft Excel (Pivot Tables, VLOOKUP, Macros preferred). Strong knowledge of SQL for data extraction and manipulation. Experience with reporting and visualization tools such as Power BI or Tableau. Solid understanding of contact center metrics (AHT, SLA, Service Level, Occupancy, etc.). Strong analytical, problem-solving, and communication skills.<br><br>Preferred Qualifications<br>Experience with WFM tools (e.g., NICE, Verint, Aspect, Genesys). Knowledge of automation tools or scripting (Python is a plus). Experience working in a high-volume customer service environment.

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p><b>Job Description</b></p><p>We are&nbsp; currently looking Data Engineer (Data Lake / Lakehouse) our Qatar operations.</p><p><br></p><p><b>Skills:</b></p><p><br></p><p>Design data lake structure, storage zones, governance, and access patterns</p><p><br></p><p>Joining time frame: 2 weeks (maximum 1 month)</p></div></section>

Role Purpose<br><br>The Senior Manager, Data Management & Governance leads client engagements that establish or strengthen practical data-management and governance capabilities. The role translates strategy and QDKC-aligned requirements into operating models, decision rights, policies, ownership and stewardship arrangements, committee practices, implementation roadmaps and performance measures that can function within the client's existing organisation.<br><br>The Senior Manager combines governance expertise with hands-on consulting delivery. This includes directing evidence collection, facilitating stakeholder agreement, managing multidisciplinary teams and ensuring that recommendations are implementable rather than theoretical. The role prepares decision material and supports governance activation, but does not assume the client's accountable roles or approval authority. Success is measured by the clarity of the operating model, the usability of the resulting artefacts, the quality of implementation support and the client's ability to sustain governance routines after handover.<br><br>Key Responsibilities<br><br>Lead governance and data-management workstreams from discovery and assessment through design, activation and handover. Assess current governance maturity, decision rights, policies, data accountabilities, controls, issues and delivery capacity using client evidence. Design target operating models covering ownership, stewardship, committees, working groups, escalation routes and delivery interfaces. Develop and quality-review governance policies, standards, charters, RACI matrices, decision records and implementation procedures. Facilitate agreement among business, technology, security, compliance and data stakeholders on responsibilities and operating rhythms. Translate strategic priorities into sequenced initiatives, roadmaps, dependencies, measures and resourcing recommendations. Coordinate governance links with cataloguing, data quality, master data, sharing, records, security, analytics and literacy workstreams. Prepare committee packs, options, recommendations and evidence summaries for decision by authorised client bodies. Establish practical registers and reporting mechanisms for issues, exceptions, decisions, actions, benefits and governance performance. Direct consultants, review deliverables, manage quality gates and maintain alignment between scope, evidence and recommendations. Support adoption through stakeholder engagement, training, communications and role-specific knowledge transfer. Track implementation progress and recommend corrective action without replacing the client's accountable owners or approvers.<br><br>Minimum Requirements<br><br>Education<br><br>Bachelor's degree in data management, information systems, business, public administration or a related field.master's degree preferred. An equivalent combination of relevant education and directly applicable consulting or implementation experience may be considered.<br><br>Professional Experience<br><br>Typically 10+ years in data governance or data management, including 4+ years managing multidisciplinary teams. Demonstrated experience designing and activating enterprise or public-sector data-governance operating models. Experience leading multidisciplinary teams and managing senior client stakeholders through policy and accountability decisions. Experience producing governance frameworks, policies, charters, RACI matrices, roadmaps and performance reports. Exposure to implementation, change management and capability transfer, not only governance assessment or documentation.<br><br>Technical and Domain Knowledge<br><br>Data-governance frameworks, operating models and decision rights. Data-management strategy, maturity assessment and implementation planning. Policy lifecycle, standards, controls, exceptions and compliance monitoring. Data ownership, stewardship and cross-functional accountability design. Metadata, data quality, master data, sharing and content-governance interfaces. Governance performance indicators, issue registers and decision records. Committee and working-group design, agendas, charters and escalation mechanisms. Public-sector stakeholder structures and national data-management expectations.<br><br>Core Competencies<br><br>Data-governance operating models. Policy and standards. Stakeholder facilitation. RACI and accountability design. Performance management. Public-sector delivery. Operating-model design. Conflict resolution. Implementation focus. Coaching. Facilitating sensitive ownership, mandate and decision-right discussions. Leading discovery interviews and converting evidence into defensible findings. Writing clear policies, operating procedures and executive recommendations. Managing workplans, quality reviews, dependencies and multidisciplinary teams. Explaining governance requirements in practical business language. Supporting adoption, training and knowledge transfer across departments. Maintaining professional challenge while respecting client decision authority.<br><br>Preferred Certifications<br><br>CDMP Practitioner or Master PMPProsci Change Practitioner<br><br>Focus areas<br><br>Data-governance operating models Policy and standards Stakeholder facilitation<br><br>Ready to apply for this role?<br><br>Apply for Senior Manager, Data Management & Governance

Role Purpose<br><br>The Director, Data Management & Security Advisory leads DAI Consultancy's portfolio of client engagements across data strategy, governance, architecture, analytics, security and value creation. The role works with executive sponsors to clarify priorities, assess organisational capability and translate national data-management expectations into achievable transformation programmes. The Director provides senior judgement on engagement scope, delivery quality, risks, dependencies and the integration of business, technology, security and change considerations.<br><br>As a senior consulting leader, the role is accountable for the quality of DAI Consultancy's advice and deliverables, the effectiveness of multidisciplinary teams and the development of trusted client relationships. The Director may facilitate executive decisions and prepare recommendations, but formal approval, ownership and risk acceptance remain with authorised client representatives. The role also supports practice development, proposal shaping, team capability and knowledge transfer so that client organisations can sustain the implemented capabilities after the engagement.<br><br>Key Responsibilities<br><br>Lead DAI Consultancy's data-management and security advisory portfolio, setting a clear service direction and quality standard for client engagements. Advise executive sponsors on data strategy, governance, security, architecture, analytics, operating-model and investment priorities. Oversee current-state, maturity and capability assessments and ensure conclusions are supported by traceable client evidence. Direct the development of target operating models, transformation roadmaps, policy portfolios, business cases and implementation plans. Integrate business, data, technology, privacy, security, regulatory and organisational-change considerations across engagement workstreams. Review major recommendations, architecture positions, risk assessments and executive deliverables before they are presented to clients. Establish engagement governance, quality gates, escalation routes and decision controls appropriate to the scope and risk of the assignment. Facilitate executive workshops and decision sessions while preserving the client's formal ownership, approval and risk-acceptance responsibilities. Monitor delivery performance, commercial health, dependencies and material risks across the portfolio and intervene when recovery action is needed. Build and maintain trusted relationships with client executives, national stakeholders, delivery partners and specialist advisers. Lead proposals, scope definition, staffing decisions and solution design for complex data and digital transformation opportunities. Coach senior managers and consultants, strengthen reusable methods and ensure knowledge is transferred to client teams at handover.<br><br>Minimum Requirements<br><br>Education<br><br>Bachelor's degree in data management, information systems, computer science, cybersecurity, business or a related field.master's degree preferred. An equivalent combination of relevant education and directly applicable consulting or implementation experience may be considered.<br><br>Professional Experience<br><br>Typically 12+ years in data, digital, technology or information governance, including 5+ years leading enterprise or public-sector functions. Demonstrated experience leading complex, multidisciplinary data, digital, technology or information-governance engagements. Experience advising executive and public-sector stakeholders on investment priorities, risk, governance and transformation sequencing. A strong record of quality-assuring strategies, operating models, roadmaps, policies, architecture positions and executive reports. Experience managing consulting portfolios, commercial performance, senior client relationships and delivery teams.<br><br>Technical and Domain Knowledge<br><br>Enterprise data strategy, governance and operating-model design. Data architecture, integration, analytics and platform concepts. Information security, privacy, classification, resilience and technology risk. Data quality, metadata, master and reference data, records and content management. Portfolio prioritisation, benefits realisation and transformation roadmapping. Public-sector governance, policy implementation and accountability structures. Executive performance measures, assurance and evidence-based decision support. Strong knowledge of the twelve Qatar Data Knowledge Case (QDKC) domains and their interdependencies.<br><br>Core Competencies<br><br>Enterprise data leadership. Government governance and policy. Risk and security oversight. Portfolio prioritization. Executive communication. Organizational change. Commercial judgement. Quality assurance. Talent development. Client relationship leadership. Executive-level facilitation, negotiation and communication. Structuring ambiguous problems and converting them into practical work programmes. Leading proposals, scoping, estimation and multidisciplinary staffing. Reviewing evidence and challenging unsupported assumptions or recommendations. Managing senior stakeholders, sensitive issues and cross-entity dependencies. Producing concise, decision-ready material for boards, committees and executive sponsors. Developing consultants and transferring capability to client teams.<br><br>Preferred Certifications<br><br>CDMP Practitioner or Master CISM or CISSPPMP or PgMP<br><br>Focus areas<br><br>Enterprise data leadership Government governance and policy Risk and security oversight<br><br>Ready to apply for this role?<br><br>Apply for Director, Data Management & Security Advisory

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Mindrift is looking for highly skilled Python Data Scraping Engineers to join the Tendem project and drive specialized data scraping workflows within our hybrid AI + human system.<br> In this role, as an AI Pilot – that’s how we </span></div>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p> <span>Start Date: </span>Immediate</p> <p> <span>Scope: </span>Whole School</p> <p> <span>Reporting to: </span>Director of Technology<br> </p> <p> <br> </p> <p>Person Profile<br>The Data Manager role combines database administration, analysis, application development, product <br>support and project management. The primary responsibilities include maintaining the school's data <br>systems, assisting departments and end-users in accessing and utilising the required data, <br>documentation of procedure and policies, and designing and implementing data systems and <br>procedures. This role is key in supporting the school's journey of deep data collection and <br>analysis.</p> <p> <br>The school's core data systems comprise of Microsoft PowerApps, iSAMS (SQL), EveryHR, Managebac, <br>Toddle, OpenApply, Microsoft SharePoint, Microsoft 365, Finalsite, LAC (Learning Analytics <br>Collaborative) and third-party web-based services and API solutions. This position offers an <br>excellent opportunity to lead the school towards a modern, user-friendly and data driven <br>institution.</p> <p> <br>He/She must seamlessly blend interpersonal skills with technical understanding. Strong <br>communication abilities are paramount to understand and address the needs of end-users with clarity <br>and empathy. Simultaneously, he/she must wield exceptional technical acumen to organise and <br>integrate data across systems. With a talent for translating user requirements into tangible <br>solutions, the ideal candidate will bridge the gap between human needs and data-driven outcomes <br>with proficiency.</p> <p> <br> </p> <p><b>Qualifications</b>. The school prefers people who:<br> have a Bachelor s degree in related field or equivalent<br> two years and above experience in student information systems or related database management <br>software required<br> have experience with school registrar (preferred)</p> <p> <br> </p> <p>Knowledge and Skills. He/She should:<br> be aligned with the ISL values of belonging, integrity, grit and kindness<br> possess strong communication skills and be willing to adapt to the demands of an international <br>school<br> be fluent in English (spoken and written)<br> have excellent communication and collaboration skills and ability to interact with a range of <br>constituents (parents, faculty, students and school leadership)<br> have strong interpersonal relations skills<br> have exceptionally high level of attention to detail<br> intermediate to high-intermediate user of MS Excel and understanding scripts and data <br>import/export files<br> have working knowledge of the Microsoft Eco-System, including Microsoft PowerApps<br> have fluency with the management of complex data<br> able to handle sensitive and confidential material with integrity<br> have willingness and ability to learn new applications<br> have proven ability to work independently within tight deadlines and strong time-management, <br>project management, and organisation skills<br> have familiarity with or experience in independent schools<br> </p> <p> <br> </p> <p><b>Responsibilities</b><br> Data Management: Oversees and maintains all databases for all record keeping in the school's <br>operations, maintains record-keeping standards, manages data system updates, and oversees data <br>transfers between systems. Responsible for data synchronisation across multiple applications and <br>ensuring efficient data flow across databases. In collaboration with the EdTech Coaches, create <br>engaging training sessions for teachers and students of varying skill levels and training <br>documentation on using and accessing the school s administrative systems.</p> <p> Database Administration and Customisation: Customises administrative systems, regularly <br>validates backups, responds to and resolves database problems and develops and maintains data <br>import and export procedures. Provides backup support to users and develops routines to facilitate <br>data usage best practices.</p> <p> System Development and Maintenance: Enhances administrative systems with custom programming such <br>as PowerApps and Visual Studio, supports administrative and academic systems with specific tools, <br>maintains data security, and develops and revises custom application. Serves as the primary contact <br>for in-house developed apps and processes and stays abreast of new technologies and approaches to <br>database management.<br> End-of-Year Rollover: Facilitates and guides the end-oy-year rollover of all databases to ensure <br>a smooth transition for each academic year. This includes technical configurations for timetable <br>and schedule readiness and ensuring the latest technical recommendations and industry standards are <br>recommended and adopted.</p> <p> Project Management: Coordinates with other Tech Hub staff and leaders and coordinates efforts of <br>data ambassadors and other experts to achieve the school s goals. Manages database installations <br>and updates, ensuring projects are delivered on time and within budget.<br> Training and Support: Provide training to the administrative staff on the use of systems, <br>supports the Tech Hub team with support tickets as required and provides support and training to <br>all users of database systems as needed.<br> Report Generation and Management: Facilitates the report card and transcript process and <br>evaluates administrative data requests, creates data collection and reports (not academic) in <br>response to business user and school needs.<br> Timetable Maintenance: Supports the preparation of the master schedule for teachers and students <br>in Early Childhood through Grade Twelve. Additionally, communicate and document configuration <br>changes to school facilities as they relate to scheduling. Work with divisional heads, department <br>leaders, and deans to support student schedule conflicts.</p> <p> System Application Management: Administers and supports the SharePoint platform, develops and <br>configures workflows and process with Microsoft PowerApps, and handles technical issues related to <br>various school management systems. Creates and regularly revises user and technical documentation <br>and procedures.<br> Interdepartmental Collaboration and cross school: Works with division administrators to maintain <br>school schedules, collaborates with ISL London remotely for system configuration consultation and <br>ensures smooth coordination and execution of various modules.</p> <p> Documentation of configuration and processes: Document all third-party and database<br></p></div></section>