Data Entry Jobs in Qatar

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.

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>

<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>

Overview<br><br>University of Doha for Science and Technology (UDST) is the first national applied University in the State of Qatar, offering applied bachelor’s and master's degrees in addition to certificates and diplomas in various fields. UDST has over 50 programs in the fields of Engineering Technology and Industrial Trades, Business Management, Computing and Information Technology, Health Sciences, Continuing and Professional Education and more.<br><br>With more than 700 staff and over 8,000 students, UDST is the destination for top-notch applied and experiential learning. The University is recognized for its student-centered learning and state-of-the-art facilities. Our faculty are committed to delivering pedagogically-sound learning experiences with incorporation of innovative technological interventions, to further enhance students’ skills and help raise talented graduates that can effectively contribute to a knowledge-based economy and make Qatar’s National Vision 2030 a reality.<br><br>The Institutional Excellence Directorate invites applications for the position of Data Analysis and Research Specialist. Reporting to the Manager, Institutional Research, the Data Analysis and Research Specialist should be a proven leader with the skills and expertise necessary to support the Institutional Excellence Directorate in fully implementing the University’s mission and vision.<br><br>Responsibilities<br><br>The successful candidate will be responsible for ensuring the demonstration of institutional effectiveness through ongoing, integrated and institution-wide research-based activities by conducting data analysis on performance of individual training providers comparative across the entity.<br><br>The successful candidate will be responsible to assist in interpreting data, analyzing results using statistical techniques, and providing analytical reports to support strategic initiatives and decision-making.<br><br>The successful candidate will contribute to the preparation of timely and accurate reports to meet the section requirements, policies and standards. S/He will also produce regular and annual reports on Institutional Effectiveness trends and areas for improvement based on data analysis.<br><br>The successful candidate will adhere to the set policies and procedures including conflict of interest, risk, complaints, data collection and management systems (including confidentiality) and report any breaches as necessary.<br><br>The successful candidate will conduct regular and ad hoc research and studies on institutional-impacting issues to support ongoing assessment toward improving Institutional effectiveness including administrative programs, academic programs, student success and student services.<br><br>The successful candidate will assist in developing and implementing database, data collection systems, data analytics and other strategies that optimize statistical efficiency and quality.<br><br>The successful candidate will assist in preparing institutional annual reports and publications and provide technical expertise on data storage structures, data mining, and data cleansing.<br><br>The successful candidate will maintain confidentiality compliance and follow all internal and governmental regulations regarding data management.<br><br>Qualifications<br><br>Education and Certifications:<br><br>Bachelor's Degree in Data Science and Analysis, Statistics or Software Engineering or another related field.<br><br>Master's Degree in a related field is preferred.<br><br>Experience:<br><br>At least 5 years relevant to duties and responsibilities at the similar level is preferred.<br><br>Language:<br><br>Fluency in written and spoken English language is required.<br><br>Fluency in written and spoken Arabic language is preferred.

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> Description <br> <br> <br> <p><span><b><span><strong>About the Role</strong></span></b></span></p><br><br><p><span><span>In this role you are expected to assist and support the team in delivering assigned audits and data analytics projects and tasks by importing, cleaning, validating and/or modelling data for the purpose of understanding it and drawing conclusions as part of ongoing audit reviews and fraud investigations.</span></span></p><br><br><p><span><b><span><strong>Your duties would include:</strong></span></b></span></p><br><br><ul><li><p><span><span>Establish and maintain effective working relationships with operational management and their teams, to be seen as a trusted advisor/partner to the QR Group.</span></span></p><br><br></li><li><p><span><span>Support the team to deliver in line with Internal Audit’s strategy, which is aligned to the strategic objectives and strategy of the QR Group.</span></span></p><br><br></li><li><p><span><span>Support team in the delivery of analysis of structured and unstructured data using various data sources, including ad-hoc projects. Highlight patterns and trends within the data by compiling and presenting these insights in a structured way.</span></span></p><br><br></li><li><p><span><span>Provide support in preparing statistical/supporting data to communicate findings, critical information and insights and inform relevant team members for recommendation setting and decision making.</span></span></p><br><br></li><li><p><span><span>Assist team in corroborating investigation facts and developing comprehensive reports with recommendations for review and decision making.</span></span></p><br><br></li><li><p><span><span>Support in the design and development of automated reporting using available corporate applications.</span></span></p><br><br></li><li><p><span><span>Assist team in identifying risks and opportunities through data analysis and inform the Line Manager.</span></span></p><br><br></li><li><p><span><span>Understand information requirements of respective IA Manager - evaluate and problem solve through data analysis by working closely with colleagues to identify data related problems.</span></span></p><br><br></li><li><p><span><span>Support in identifying valuable data sources available within the company and understanding interrelations between different datasets. Also ensure that all data handling measures are adhered to at all times.</span></span></p><br><br></li><li><p><span><span>Use ACL and other available analytical tools, write and develop scripts that support in the automation, processing, cleansing, and verifying of the data integrity.</span></span></p><br><br></li><li><p><span><span>Ensure that all information that is provided through analysis is timely, accurate and highlights areas of opportunity or risk to the business, (where relevant).</span></span></p><br><br></li><li><p><span><span>Participate in high value/high risk (both planned and adhoc) related to specialist area by helping to identify non-compliance to QR policies and procedures in this area. Understand all policies and procedures related to specialized area and the impact they have on QR business.</span></span></p><br><br></li><li><p><span><span>Perform complex tests related to specialized area. Ensure that all tests conducted are backed up by robust supporting documentation.</span></span></p><br><br></li><li><p><span><span>Communicate effectively with relevant stakeholders to support team in collaboration of IA reviews.</span></span></p><br><br></li></ul><p><span><b><span><strong>Be part of an extraordinary story</strong></span></b></span></p><br><br><p><span><span>Your skills. Your imagination. Your ambition. Here, there are no boundaries to your potential and the impact you can make.</span><span>You’ll find infinite opportunities to grow and work on the biggest, most rewarding challenges that will build your skills and experience. You have the chance to be a part of our future and build the life you want while being part of an international community.</span></span></p><br><br><p><span><span>Our best is here and still to come. To us, impossible is only a challenge. Join us as we dare to achieve what’s never been done before.</span></span></p><br><br><p><span><span>Together, everything is possible.</span></span></p><br><br><br> <br> <br> <br> <br> <br> General Information <br> <br> Ref # <br> 2600007F <br> <br> Location <br> Qatar-Doha <br> <br> Job family <br> Corporate &amp; Commercial <br> <br> <ul><li><span>Closing Date:</span> <span>2026-06-08</span></li></ul><br> <br> <br> <br> <br> <br> </div>

<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 refer to this role at Mindrift – you’ll collaborate with Tendem Agents that handle repetitive tasks, while you provide critical thinking, domain expertise, and quality control to deliver accurate and actionable results.<br> This part-time remote opportunity is ideal for technical professionals with hands-on experience in web scraping, data extraction and processing.<br> What We Do The Mindrift platform connects specialists with AI projects from major tech innovators.<br> Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.<br> About the Role This is a freelance role for a Tendem project.<br> As a Python Data Scraping Engineer, you'll handle data scraping tasks requiring technical precision for web extraction and processing, utilizing various tools such as our provided Apify and OpenRouter alongside your own resourceful approaches.<br> Key Responsibilities Own end-to-end data extraction workflows across complex websites, ensuring complete coverage, accuracy, and reliable delivery of structured datasets.<br> Leverage internal tools (Apify, OpenRouter) alongside custom workflows to accelerate data collection, validation, and task execution while meeting defined requirements.<br> Ensure reliable extraction from dynamic and interactive web sources, adapting approaches as needed to handle JavaScript-rendered content and changing site behavior.<br> Enforce data quality standards through validation checks, cross-source consistency controls, adherence to formatting specifications, and systematic verification prior to delivery.<br> Scale scraping operations for large datasets using efficient batching or parallelization, monitor failures, and maintain stability against minor site structure changes.<br> Compensation On this project, contributors can earn up to $37 per hour equivalent , depending on their level and pace of contribution.<br> Compensation varies across projects depending on scope, complexity, and required expertise.<br> Please note that other projects on the platform may offer different earning levels based on their requirements.<br> How to get started Simply apply to this post, qualify, and get the chance to contribute to projects that match your technical skills, on your own schedule.<br> From coding and automation to fine-tuning AI outputs, you’ll play a key role in advancing AI capabilities and real-world applications.<br> Why this freelance opportunity might be a great fit for you?<br> Work fully remote on your own schedule with just a laptop and stable internet connection.<br> Gain hands-on experience in a unique hybrid environment where human expertise and AI agents collaborate seamlessly — a distinctive skill set in a rapidly growing field.<br> Participate in performance-based bonus programs that reward high-quality work and consistent delivery.<br> At least 3 year of relevant experience in data engineering, web scraping, automation, or software development (required).<br> Bachelor's or Master’s Degree in Engineering, Applied Mathematics, Computer Science, or related technical fields is a plus.<br> Strong experience in Python web scraping (BeautifulSoup, Selenium or similar), including dynamic content (JS, AJAX, infinite scroll) and APIs via proxies.<br> Proven ability to extract data from complex structures (hierarchies, archived pages, inconsistent HTML).<br> Solid background in data cleaning, normalization, and validation, delivering structured datasets (CSV, JSON, Google Sheets).<br> Hands-on experience with LLMs and AI frameworks to enhance automation and problem-solving.<br> Strong attention to detail and commitment to data accuracy.<br> Self-directed work ethic with ability to troubleshoot independently.<br> A link to GitHub is a plus.<br> English proficiency: Upper-intermediate (B2) or above (required).<br></span> </div>

<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 refer to this role at Mindrift – you’ll collaborate with Tendem Agents that handle repetitive tasks, while you provide critical thinking, domain expertise, and quality control to deliver accurate and actionable results.<br> This part-time remote opportunity is ideal for technical professionals with hands-on experience in web scraping, data extraction and processing.<br> What We Do The Mindrift platform connects specialists with AI projects from major tech innovators.<br> Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.<br> About the Role This is a freelance role for a Tendem project.<br> As a Python Data Scraping Engineer, you'll handle data scraping tasks requiring technical precision for web extraction and processing, utilizing various tools such as our provided Apify and OpenRouter alongside your own resourceful approaches.<br> Key Responsibilities Own end-to-end data extraction workflows across complex websites, ensuring complete coverage, accuracy, and reliable delivery of structured datasets.<br> Leverage internal tools (Apify, OpenRouter) alongside custom workflows to accelerate data collection, validation, and task execution while meeting defined requirements.<br> Ensure reliable extraction from dynamic and interactive web sources, adapting approaches as needed to handle JavaScript-rendered content and changing site behavior.<br> Enforce data quality standards through validation checks, cross-source consistency controls, adherence to formatting specifications, and systematic verification prior to delivery.<br> Scale scraping operations for large datasets using efficient batching or parallelization, monitor failures, and maintain stability against minor site structure changes.<br> Compensation On this project, contributors can earn up to $37 per hour equivalent , depending on their level and pace of contribution.<br> Compensation varies across projects depending on scope, complexity, and required expertise.<br> Please note that other projects on the platform may offer different earning levels based on their requirements.<br> How to get started Simply apply to this post, qualify, and get the chance to contribute to projects that match your technical skills, on your own schedule.<br> From coding and automation to fine-tuning AI outputs, you’ll play a key role in advancing AI capabilities and real-world applications.<br> Why this freelance opportunity might be a great fit for you?<br> Work fully remote on your own schedule with just a laptop and stable internet connection.<br> Gain hands-on experience in a unique hybrid environment where human expertise and AI agents collaborate seamlessly — a distinctive skill set in a rapidly growing field.<br> Participate in performance-based bonus programs that reward high-quality work and consistent delivery.<br> At least 3 year of relevant experience in data engineering, web scraping, automation, or software development (required).<br> Bachelor's or Master’s Degree in Engineering, Applied Mathematics, Computer Science, or related technical fields is a plus.<br> Strong experience in Python web scraping (BeautifulSoup, Selenium or similar), including dynamic content (JS, AJAX, infinite scroll) and APIs via proxies.<br> Proven ability to extract data from complex structures (hierarchies, archived pages, inconsistent HTML).<br> Solid background in data cleaning, normalization, and validation, delivering structured datasets (CSV, JSON, Google Sheets).<br> Hands-on experience with LLMs and AI frameworks to enhance automation and problem-solving.<br> Strong attention to detail and commitment to data accuracy.<br> Self-directed work ethic with ability to troubleshoot independently.<br> A link to GitHub is a plus.<br> English proficiency: Upper-intermediate (B2) or above (required).<br></span> </div>

Hiring Now: Multiple Hyperscale Data Center Vacancies in Qatar & Saudi Arabia<br>As part of Mannai Corporation’s continued regional expansion, we are hiring experienced professionals to join our MEP and ELV project teams for hyperscale data center projects in Qatar and Saudi Arabia.<br>Candidates with strong experience in hyperscale data centers, mission-critical facilities, or complex MEP infrastructure projects are invited to apply.<br>Face-to-Face Interview Drive – India???? Hyderabad???? Chennai???? Tentatively scheduled for the first week of August 2026<br>Shortlisted candidates will have the opportunity to meet directly with our project leadership and recruitment teams.<br>Job Purpose The selected professionals will support the planning, execution, commissioning, and successful delivery of hyperscale data center construction projects.<br>Open Positions• Senior Project Manager• Data Center Systems Manager• Construction Manager• QA/QC Manager• HSE & Security Manager• Technical Manager• Planning Manager• Testing & Commissioning Manager• Commercial & Contracts Manager• Procurement Engineers• UPS Field Service Engineer• Data Center Cooling Product Field Service Engineer• Auto CAD Draftsmen• Quantity Surveyors<br>Key Responsibilities• Support the planning and delivery of data center construction projects.• Coordinate with consultants, contractors, vendors, and project stakeholders.• Monitor project schedules, budgets, quality standards, and deliverables.• Review engineering drawings, technical submittals, and construction documents.• Ensure compliance with project specifications, safety standards, and applicable codes.• Manage site activities and resolve technical and operational issues.• Support testing, commissioning, handover, procurement, and material coordination.• Prepare progress reports and technical documentation.<br>Qualifications and Experience• Proven experience in hyperscale data centers or mission-critical infrastructure projects is mandatory.• 5–15+ years of relevant experience, depending on the position.• Bachelor’s degree or diploma in Electrical, Mechanical, Civil Engineering, Construction Management, Quantity Surveying, or a related discipline.• Strong understanding of MEP systems, construction methodologies, and the full project lifecycle.• Experience working with international standards and industry best practices.• Professional certifications such as PMP, LEED, NEBOSH, OSHA, Autodesk BIM, or equivalent will be an advantage.<br>Take the next step in your career and be part of landmark hyperscale data center projects in Qatar.<br>Reach out to us at mcw-support@mannai.com.qa

Hiring Now: Multiple Hyperscale Data Center Vacancies in Qatar & Saudi Arabia<br>As part of Mannai Corporation’s continued regional expansion, we are hiring experienced professionals to join our MEP and ELV project teams for hyperscale data center projects in Qatar and Saudi Arabia.<br>Candidates with strong experience in hyperscale data centers, mission-critical facilities, or complex MEP infrastructure projects are invited to apply.<br>Face-to-Face Interview Drive – India???? Hyderabad???? Chennai???? Tentatively scheduled for the first week of August 2026<br>Shortlisted candidates will have the opportunity to meet directly with our project leadership and recruitment teams.<br>Job Purpose The selected professionals will support the planning, execution, commissioning, and successful delivery of hyperscale data center construction projects.<br>Open Positions• Senior Project Manager• Data Center Systems Manager• Construction Manager• QA/QC Manager• HSE & Security Manager• Technical Manager• Planning Manager• Testing & Commissioning Manager• Commercial & Contracts Manager• Procurement Engineers• UPS Field Service Engineer• Data Center Cooling Product Field Service Engineer• Auto CAD Draftsmen• Quantity Surveyors<br>Key Responsibilities• Support the planning and delivery of data center construction projects.• Coordinate with consultants, contractors, vendors, and project stakeholders.• Monitor project schedules, budgets, quality standards, and deliverables.• Review engineering drawings, technical submittals, and construction documents.• Ensure compliance with project specifications, safety standards, and applicable codes.• Manage site activities and resolve technical and operational issues.• Support testing, commissioning, handover, procurement, and material coordination.• Prepare progress reports and technical documentation.<br>Qualifications and Experience• Proven experience in hyperscale data centers or mission-critical infrastructure projects is mandatory.• 5–15+ years of relevant experience, depending on the position.• Bachelor’s degree or diploma in Electrical, Mechanical, Civil Engineering, Construction Management, Quantity Surveying, or a related discipline.• Strong understanding of MEP systems, construction methodologies, and the full project lifecycle.• Experience working with international standards and industry best practices.• Professional certifications such as PMP, LEED, NEBOSH, OSHA, Autodesk BIM, or equivalent will be an advantage.<br>Take the next step in your career and be part of landmark hyperscale data center projects in Qatar.<br>Reach out to us at mcw-support@mannai.com.qa

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Mindrift is looking for highly skilled Senior 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 refer to this role at Mindrift – you’ll collaborate with Tendem Agents that handle repetitive tasks, while you provide critical thinking, domain expertise, and quality control to deliver accurate and actionable results.<br> This part-time remote opportunity is ideal for technical professionals with hands-on experience in web scraping, data extraction and processing.<br> What We Do The Mindrift platform connects specialists with AI projects from major tech innovators.<br> Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.<br> This is a freelance role for a Tendem project.<br> As a Senior Python Data Scraping Engineer , you'll handle data scraping tasks requiring technical precision for web extraction and processing, utilizing various tools such as our provided Apify and OpenRouter alongside your own resourceful approaches.<br> Key Responsibilities: Own end-to-end data extraction workflows across complex websites, ensuring complete coverage, accuracy, and reliable delivery of structured datasets.<br> Leverage internal tools (Apify, OpenRouter) alongside custom workflows to accelerate data collection, validation, and task execution while meeting defined requirements.<br> Ensure reliable extraction from dynamic and interactive web sources, adapting approaches as needed to handle JavaScript-rendered content and changing site behavior.<br> Enforce data quality standards through validation checks, cross-source consistency controls, adherence to formatting specifications, and systematic verification prior to delivery.<br> Scale scraping operations for large datasets using efficient batching or parallelization, monitor failures, and maintain stability against minor site structure changes.<br> Requirements: At least 5+ years of relevant experience in data engineering, web scraping, automation, or software development (required).<br> Bachelor’s or Master’s Degree in Engineering, Applied Mathematics, Computer Science, or related technical fields is a plus.<br> Candidates should have a strong technical foundation and practical experience with scripting, automation, and AI-assisted workflows.<br> We are looking for specialists who can solve non-trivial problems, work confidently with LLMs, and systematically collect, structure, and validate data from diverse sources.<br> A methodical, detail-oriented approach and the ability to work independently are essential.<br> Strong experience in Python web scraping (BeautifulSoup, Selenium or similar), including dynamic content (JS, AJAX, infinite scroll) and APIs via proxies Proven ability to extract data from complex structures (hierarchies, archived pages, inconsistent HTML) Solid background in data cleaning, normalization, and validation, delivering structured datasets (CSV, JSON, Google Sheets) Demonstrated experience handling anti-bot mechanisms and dynamic site structures at scale Experience with cloud infrastructure (AWS or equivalent) and containerization (Docker) as part of real workflows Hands-on experience with LLM frameworks (LangChain, OpenRouter, or similar) applied to automation tasks Strong attention to detail and commitment to data accuracy Self-directed work ethic with ability to troubleshoot independently A link to GitHub is a plus English proficiency: Upper-intermediate (B2) or above (required) Project time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements.<br> This is an estimate, not a guaranteed workload, and applies only while the project is active.<br> Compensation On this project, contributors can earn up to $37 per hour equivalent , depending on their level and pace of contribution.<br> Compensation varies across projects depending on scope, complexity, and required expertise.<br> Please note that other projects on the platform may offer different earning levels based on their requirements.<br></span> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> Description <br> <br> <br> <p><strong><u>About the role:</u></strong></p><br><br><p><span><span>Responsible for providing pro-active and reactive data and operational performance analysis and monitoring, as well as importing, cleaning, transforming, validating, and/ or modeling data to generate operational</span><span>reports</span><span>and</span><span>dashboards</span><span>that</span><span>serve</span><span>as</span><span>a</span><span>tool</span><span>for</span><span>analyzing</span><span>and</span><span>understanding</span><span>the</span><span>operational performance, outcomes and conclusions that help for planning and decision-making purposes.</span></span></p><br><br><ul><li><p><span><span>Provide</span><span>technical</span><span>expertise</span><span>to</span><span>the</span><span>information</span><span>system</span><span>team</span><span>in</span><span>major</span><span>application</span><span>deployment</span><span>by</span><span>assisting</span><span>in designing process to arrive at high performance and optimal operational solutions.</span></span></p><br><br></li><li><p><span><span>Develop</span><span>operational</span><span>dashboards,</span><span>analysis</span><span>and</span><span>reports</span><span>related</span><span>to</span><span>customer</span><span>experience</span><span>data</span><span>for</span><span>the management team and individual stakeholders.</span></span></p><br><br></li><li><p><span><span>Reduce</span><span>manual</span><span>operational</span><span>jobs</span><span>by</span><span>ensuring</span><span>automation</span><span>of</span><span>as</span><span>many</span><span>operational</span><span>procedures</span><span>that</span><span>are</span><span>used for monitoring and supporting databases.</span></span></p><br><br></li><li><p><span><span>Improve</span><span>data</span><span>quality</span><span>through</span><span>data</span><span>cleaning and</span><span>filtering</span><span>out</span><span>the</span><span>irrelevant</span><span>data</span><span>to</span><span>the</span><span> business.</span></span></p><br><br></li><li><p><span><span>Produce reports and analysis through presentations and/or dynamic dashboards on the internal performance</span><span>of</span><span>the</span><span>Operations</span><span>department</span><span>against</span><span>the</span><span>set</span><span>KPIs.</span><span>Ensure</span><span>that</span><span>this</span><span>information</span><span>is</span><span>timely, accurate and highlights areas of opportunity or risk to the business.</span></span></p><br><br></li><li><p><span><span>Proactively</span><span>identify</span><span>any</span><span>source</span><span>of</span><span>data</span><span>discrepancy</span><span>and</span><span>develop</span><span>solutions</span><span>for</span><span>prevention</span><span>of</span><span>future </span><span>discrepancy.</span></span></p><br><br></li><li><p><span><span>Analyze</span><span>information</span><span>using</span><span>various</span><span>statistical</span><span>methods and</span><span>highlight</span><span>patterns</span><span>and</span><span>trends</span><span>within</span><span>the</span><span>data</span><span>to suggest conclusions.</span></span></p><br><br></li><li><p><span><span>Support Line Manager and team by designing and presenting the gained </span><span>conclusions.</span></span></p><br><br></li><li><p><span><span>Develop</span><span>statistical</span><span>/</span><span>supporting</span><span>database</span><span>requested</span><span>or</span><span>needed</span><span>by</span><span>the</span><span>management,</span><span>which</span><span>can</span><span>be</span><span>easily presented through presentations, business cases or management information reports.</span></span></p><br><br></li><li><p><span><span>Attend</span><span>Daily</span><span>/</span><span>Weekly</span><span>/</span><span>Monthly</span><span>meetings</span><span>with</span><span>managers</span><span>to</span><span>understand</span><span>the</span><span>business</span><span>requirements.</span><span>Meet with the business to discuss operational projects and identify current and required data that will help the business to set the KPI’s outlined by the management.</span></span></p><br><br></li><li><p><span><span>Design/develop</span><span>automated</span><span>reporting</span><span>using</span><span>SharePoint,</span><span>Power</span><span>BI</span><span>and</span><span>other</span><span>corporate</span><span>applications, enabling to capture, analyze and present the data.</span></span></p><br><br></li><li><p><span><span>Provide</span><span>front</span><span>line</span><span>staff</span><span>within</span><span>the</span><span>operations</span><span>department,</span><span>guidance</span><span>on</span><span>how</span><span>to</span><span>use</span><span>applicable</span><span>management systems and tools, and how and when to record data ensuring procedures and controls are enforced to enable efficient recording and presentation of such data.</span></span></p><br><br></li></ul> <br> <br> <br> <br> <br> General Information <br> <br> Ref # <br> 226971 <br> <br> Location <br> Qatar-Doha <br> <br> Job family <br> Cargo &amp; Airport Operations <br> <br> <ul><li><span>Closing Date:</span> <span>2026-06-01</span></li></ul><br> <br> <br> <br> <br> <br> </div>

Job Description<br><br>Must Have<br><br> 6–10 years of experience in data science, analytics, or applied statistics, including a demonstrable track record of leading projects end to end. Senior technical voice on a data science team — setting modeling standards, reviewing peer work, and mentoring less-experienced data scientists. Deep command of statistics, experimental design, and a broad modeling toolkit spanning classical machine learning, time-series, and deep learning. Demonstrated ability to translate ambiguous business and policy questions into rigorous, decision-ready analysis for executive audiences. Commitment to statistical soundness, reproducibility, and continuous learning in statistical and machine-learning methods. <br><br>Nice to have<br><br> Experience in the government or large-enterprise sector, ideally in Qatar or the wider GCC. Familiarity with Oracle Cloud Infrastructure (OCI) and cloud-based analytics environments. Exposure to deploying models into production in partnership with engineering teams. Domain expertise in a relevant vertical such as public sector, finance, telecom, or healthcare. Experience with causal inference or advanced experimentation methods. Working knowledge of data visualization or business-intelligence tools for stakeholder communication. Relevant data science or cloud certifications. <br><br>Responsibilities<br><br> Lead the design and execution of advanced analytics and statistical modeling projects, from problem framing through to validated, decision-ready insight. Translate ambiguous business and policy questions into well-defined data science problems, measurable hypotheses, and analytical plans. Define and enforce modeling methodology, experimentation standards (including A/B testing and quasi-experimental designs), and model validation practices across the team. Build, evaluate, and interpret advanced predictive and statistical models using Python (pandas, scikit-learn, statsmodels) and SQL. Select appropriate techniques across regression, classification, clustering, time-series, deep learning, and causal inference, and justify trade-offs to stakeholders. Own the statistical soundness of analytical deliverables, including assumptions, uncertainty quantification, and limitations. Establish reproducible analytical workflows and promote good practice in code quality, documentation, and version control within the team. Present findings and recommendations to senior, often non-technical, stakeholders through clear narratives and visualizations that drive decisions. Review and provide technical feedback on the analytical work of data scientists, raising the overall standard of the team. Mentor and coach junior and mid-level data scientists, supporting their technical and professional growth. Partner with machine-learning and AI engineers to hand off validated models for productionization and to define monitoring and success metrics. Contribute to proposals, scoping, and effort estimation for new data science engagements. <br><br>Qualifications<br><br> Bachelor's degree in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative field; Master's or PhD preferred. Deep proficiency in Python for analysis and the scientific stack (pandas, Num Py, scikit-learn, statsmodels) and strong SQL. Strong foundation in statistics and experimental design, with command of a broad range of modeling techniques. Hands-on experience applying deep learning and neural network architectures using frameworks such as Tensor Flow or PyTorch. Experience designing and interpreting experiments and translating results into business recommendations. Demonstrated ability to frame business problems and communicate analytical results to executive and non-technical audiences. Experience mentoring analysts or data scientists and setting analytical standards or methodology. Strong understanding of the end-to-end data science lifecycle, including data quality, validation, and model handoff. Ability to manage multiple workstreams and stakeholders simultaneously.

Job Description<br><br>Must Have<br><br> 6–10 years of experience in data science, analytics, or applied statistics, including a demonstrable track record of leading projects end to end. Senior technical voice on a data science team — setting modeling standards, reviewing peer work, and mentoring less-experienced data scientists. Deep command of statistics, experimental design, and a broad modeling toolkit spanning classical machine learning, time-series, and deep learning. Demonstrated ability to translate ambiguous business and policy questions into rigorous, decision-ready analysis for executive audiences. Commitment to statistical soundness, reproducibility, and continuous learning in statistical and machine-learning methods. <br><br>Nice to have<br><br> Experience in the government or large-enterprise sector, ideally in Qatar or the wider GCC. Familiarity with Oracle Cloud Infrastructure (OCI) and cloud-based analytics environments. Exposure to deploying models into production in partnership with engineering teams. Domain expertise in a relevant vertical such as public sector, finance, telecom, or healthcare. Experience with causal inference or advanced experimentation methods. Working knowledge of data visualization or business-intelligence tools for stakeholder communication. Relevant data science or cloud certifications. <br><br>Responsibilities<br><br> Lead the design and execution of advanced analytics and statistical modeling projects, from problem framing through to validated, decision-ready insight. Translate ambiguous business and policy questions into well-defined data science problems, measurable hypotheses, and analytical plans. Define and enforce modeling methodology, experimentation standards (including A/B testing and quasi-experimental designs), and model validation practices across the team. Build, evaluate, and interpret advanced predictive and statistical models using Python (pandas, scikit-learn, statsmodels) and SQL. Select appropriate techniques across regression, classification, clustering, time-series, deep learning, and causal inference, and justify trade-offs to stakeholders. Own the statistical soundness of analytical deliverables, including assumptions, uncertainty quantification, and limitations. Establish reproducible analytical workflows and promote good practice in code quality, documentation, and version control within the team. Present findings and recommendations to senior, often non-technical, stakeholders through clear narratives and visualizations that drive decisions. Review and provide technical feedback on the analytical work of data scientists, raising the overall standard of the team. Mentor and coach junior and mid-level data scientists, supporting their technical and professional growth. Partner with machine-learning and AI engineers to hand off validated models for productionization and to define monitoring and success metrics. Contribute to proposals, scoping, and effort estimation for new data science engagements. <br><br>Qualifications<br><br> Bachelor's degree in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative field; Master's or PhD preferred. Deep proficiency in Python for analysis and the scientific stack (pandas, Num Py, scikit-learn, statsmodels) and strong SQL. Strong foundation in statistics and experimental design, with command of a broad range of modeling techniques. Hands-on experience applying deep learning and neural network architectures using frameworks such as Tensor Flow or PyTorch. Experience designing and interpreting experiments and translating results into business recommendations. Demonstrated ability to frame business problems and communicate analytical results to executive and non-technical audiences. Experience mentoring analysts or data scientists and setting analytical standards or methodology. Strong understanding of the end-to-end data science lifecycle, including data quality, validation, and model handoff. Ability to manage multiple workstreams and stakeholders simultaneously.

Job Description<br><br>Must Have<br><br> 6–10 years of experience in data science, analytics, or applied statistics, including a demonstrable track record of leading projects end to end. Senior technical voice on a data science team — setting modeling standards, reviewing peer work, and mentoring less-experienced data scientists. Deep command of statistics, experimental design, and a broad modeling toolkit spanning classical machine learning, time-series, and deep learning. Demonstrated ability to translate ambiguous business and policy questions into rigorous, decision-ready analysis for executive audiences. Commitment to statistical soundness, reproducibility, and continuous learning in statistical and machine-learning methods. <br><br>Nice to have<br><br> Experience in the government or large-enterprise sector, ideally in Qatar or the wider GCC. Familiarity with Oracle Cloud Infrastructure (OCI) and cloud-based analytics environments. Exposure to deploying models into production in partnership with engineering teams. Domain expertise in a relevant vertical such as public sector, finance, telecom, or healthcare. Experience with causal inference or advanced experimentation methods. Working knowledge of data visualization or business-intelligence tools for stakeholder communication. Relevant data science or cloud certifications. <br><br>Responsibilities<br><br> Lead the design and execution of advanced analytics and statistical modeling projects, from problem framing through to validated, decision-ready insight. Translate ambiguous business and policy questions into well-defined data science problems, measurable hypotheses, and analytical plans. Define and enforce modeling methodology, experimentation standards (including A/B testing and quasi-experimental designs), and model validation practices across the team. Build, evaluate, and interpret advanced predictive and statistical models using Python (pandas, scikit-learn, statsmodels) and SQL. Select appropriate techniques across regression, classification, clustering, time-series, deep learning, and causal inference, and justify trade-offs to stakeholders. Own the statistical soundness of analytical deliverables, including assumptions, uncertainty quantification, and limitations. Establish reproducible analytical workflows and promote good practice in code quality, documentation, and version control within the team. Present findings and recommendations to senior, often non-technical, stakeholders through clear narratives and visualizations that drive decisions. Review and provide technical feedback on the analytical work of data scientists, raising the overall standard of the team. Mentor and coach junior and mid-level data scientists, supporting their technical and professional growth. Partner with machine-learning and AI engineers to hand off validated models for productionization and to define monitoring and success metrics. Contribute to proposals, scoping, and effort estimation for new data science engagements. <br><br>Qualifications<br><br> Bachelor's degree in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative field; Master's or PhD preferred. Deep proficiency in Python for analysis and the scientific stack (pandas, Num Py, scikit-learn, statsmodels) and strong SQL. Strong foundation in statistics and experimental design, with command of a broad range of modeling techniques. Hands-on experience applying deep learning and neural network architectures using frameworks such as Tensor Flow or PyTorch. Experience designing and interpreting experiments and translating results into business recommendations. Demonstrated ability to frame business problems and communicate analytical results to executive and non-technical audiences. Experience mentoring analysts or data scientists and setting analytical standards or methodology. Strong understanding of the end-to-end data science lifecycle, including data quality, validation, and model handoff. Ability to manage multiple workstreams and stakeholders simultaneously.

<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 refer to this role at Mindrift – you’ll collaborate with Tendem Agents that handle repetitive tasks, while you provide critical thinking, domain expertise, and quality control to deliver accurate and actionable results.<br> This part-time remote opportunity is ideal for technical professionals with hands-on experience in web scraping, data extraction and processing.<br> What We Do The Mindrift platform connects specialists with AI projects from major tech innovators.<br> Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.<br> About the Role This is a freelance role for a Tendem project.<br> As a Python Data Scraping Engineer, you'll handle data scraping tasks requiring technical precision for web extraction and processing, utilizing various tools such as our provided Apify and OpenRouter alongside your own resourceful approaches.<br> Key Responsibilities Own end-to-end data extraction workflows across complex websites, ensuring complete coverage, accuracy, and reliable delivery of structured datasets.<br> Leverage internal tools (Apify, OpenRouter) alongside custom workflows to accelerate data collection, validation, and task execution while meeting defined requirements.<br> Ensure reliable extraction from dynamic and interactive web sources, adapting approaches as needed to handle JavaScript-rendered content and changing site behavior.<br> Enforce data quality standards through validation checks, cross-source consistency controls, adherence to formatting specifications, and systematic verification prior to delivery.<br> Scale scraping operations for large datasets using efficient batching or parallelization, monitor failures, and maintain stability against minor site structure changes.<br> Compensation On this project, contributors can earn up to $37 per hour equivalent , depending on their level and pace of contribution.<br> Compensation varies across projects depending on scope, complexity, and required expertise.<br> Please note that other projects on the platform may offer different earning levels based on their requirements.<br> How to get started Simply apply to this post, qualify, and get the chance to contribute to projects that match your technical skills, on your own schedule.<br> From coding and automation to fine-tuning AI outputs, you’ll play a key role in advancing AI capabilities and real-world applications.<br> Why this freelance opportunity might be a great fit for you?<br> Work fully remote on your own schedule with just a laptop and stable internet connection.<br> Gain hands-on experience in a unique hybrid environment where human expertise and AI agents collaborate seamlessly — a distinctive skill set in a rapidly growing field.<br> Participate in performance-based bonus programs that reward high-quality work and consistent delivery.<br> At least 3 year of relevant experience in data engineering, web scraping, automation, or software development (required).<br> Bachelor's or Master’s Degree in Engineering, Applied Mathematics, Computer Science, or related technical fields is a plus.<br> Strong experience in Python web scraping (BeautifulSoup, Selenium or similar), including dynamic content (JS, AJAX, infinite scroll) and APIs via proxies.<br> Proven ability to extract data from complex structures (hierarchies, archived pages, inconsistent HTML).<br> Solid background in data cleaning, normalization, and validation, delivering structured datasets (CSV, JSON, Google Sheets).<br> Hands-on experience with LLMs and AI frameworks to enhance automation and problem-solving.<br> Strong attention to detail and commitment to data accuracy.<br> Self-directed work ethic with ability to troubleshoot independently.<br> A link to GitHub is a plus.<br> English proficiency: Upper-intermediate (B2) or above (required).<br></span> </div>