Python Developer Jobs in Qatar
410 Jobs Found
Qatar - Doha
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
Qatar - Doha
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
Qatar - Doha
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
Qatar - Doha
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
Qatar - Doha
???? Welcome to Your Next Adventure!<br><br>We are looking for a Senior AI Engineer to join Snoonu's R&D team as a technical anchor for our conversational AI and agentic automation strategy. You will lead the design and delivery of production-grade chatbot systems powered by AWS and frontier LLMs (Claude-first), and architect Agentic AI pipelines that encode Snoonu's SOPs into autonomous, reliable workflows across customer support, order verification, and logistics. Beyond building, you will set technical standards, guide junior engineers, and act as a key decision-maker in choosing the next technology directions the team will discover and dominate.<br><br>???? What You’ll Get Your Hands On<br><br>Technical Leadership & Architecture<br><br>Own the end-to-end architecture of Snoonu's conversational AI and agentic automation platform — from LLM selection and prompt strategy to cloud infrastructure and observability. Define engineering standards, design patterns, and best practices for AI system development; conduct design reviews and enforce quality bars. Mentor and guide junior/mid-level engineers; review code, provide technical feedback, and accelerate the team's LLM engineering capabilities. Partner directly with the R&D Director to evaluate emerging technologies, shape the team's technical roadmap, and present recommendations with trade-off analysis.<br><br>Conversational AI & Chatbot Development<br><br>Lead the design and delivery of multi-channel chatbots (web, Whats App, app) using AWS Lex, Bedrock, and API Gateway integrated with Claude or other LLMs. Own complex dialogue system challenges: multi-turn reasoning, context persistence, intent disambiguation, and graceful fallback strategies. Integrate chatbots with Snoonu's backend services (order management, CRM, logistics APIs) via secure, scalable RESTful/event-driven patterns. Drive LLM evaluation cycles — benchmark model versions, prompt strategies, and RAG configurations against production quality and cost targets.<br><br>Agentic AI Pipelines<br><br>Architect Agentic AI systems that encode Snoonu SOPs as autonomous, multi-step workflows for customer support, order verification, and logistics operations. Select and govern the right orchestration approach (Lang Graph, Crew AI, Bedrock Agents, Step Functions) per use case — with a clear rationale on reliability, debuggability, and scalability. Design robust memory, context management, tool-use, and guardrail layers to ensure agents behave predictably in adversarial or edge-case conditions. Establish human-in-the-loop checkpoints, confidence thresholds, and escalation paths — ensuring agents augment rather than replace human judgment in critical decisions.<br><br>AWS Infrastructure & MLOps<br><br>Design and own the cloud backbone for AI services: Lambda, ECS/Fargate, SQS/SNS, Dynamo DB, S3, Cloud Watch, and Bedrock — with a focus on scalability, cost, and reliability. Build CI/CD pipelines for prompt versioning, model rollout, A/B testing, and automated evals before production deployment. Define and enforce monitoring standards for drift, latency, cost, and failure rates across all deployed AI systems.<br><br>R&D & Innovation<br><br>Lead frontier model evaluation — benchmark Claude, GPT, LLaMA, Mistral, and emerging open-weight models against Snoonu's specific use cases and constraints. Identify and prototype the next high-leverage AI capability the team should build — bring experiments from idea to validated proof-of-concept with clear go/no-go criteria. Produce high-quality technical documentation: architecture decision records, experimental results, and prompt engineering playbooks for team-wide use.<br><br>????♂️ The Magic You Bring<br><br>Education<br><br>Bachelor's or Master's degree in Computer Science, AI, Software Engineering, or a related field.<br><br>Experience<br><br>5–8 years of hands-on software engineering experience, with at least 3 years focused on LLM-based systems, conversational AI, or agentic architectures. Demonstrated track record of owning and shipping production AI systems end-to-end — not just models, but the full stack from API to monitoring. Portfolio, Git Hub, or detailed case studies required. Prior experience in a senior IC or tech lead role: setting technical direction, conducting design reviews, and mentoring engineers. Strong Python and backend development skills (Fast API / Flask preferred); ability to write clean, production-grade, maintainable code. Research-driven mindset — obsessed with what's next in AI; able to translate frontier research into production value quickly. Extreme ownership: you define the problem, architect the solution, ship it, and hold yourself accountable for outcomes — without waiting to be told. Strong business context awareness — you think about ROI, operational impact, and user outcomes, not just technical elegance. Senior communicator: can explain complex agent design trade-offs to non-engineers, write compelling technical proposals, and influence direction through clarity of thought. Thrives in ambiguity — can operate effectively in fast-paced R&D environments where the problem definition evolves alongside the solution. Natural multiplier: makes the engineers around them better through code reviews, design feedback, and knowledge sharing. Collaborative and direct — comfortable pushing back on requirements and raising risks early, not just executing orders.<br><br>LLMs & Generative AI (Core)<br><br>Deep experience with Anthropic Claude (claude-3 / claude-sonnet / claude-opus) via API and AWS Bedrock — prompt engineering, tool use, and multi-turn reasoning. Familiarity with Open AI GPT models and open-weight models (LLaMA 3, Mistral, Phi) — fine-tuning, quantization, and local inference is a strong plus. Retrieval-Augmented Generation (RAG): vector databases (Open Search, Pinecone, pgvector), embedding models, and hybrid search. Agentic frameworks: Lang Chain / Lang Graph, Crew AI, Auto Gen, or AWS Bedrock Agents. Prompt engineering, system prompt design, evaluation (evals), and red-teaming for production safety.<br><br>AWS Services (Core)<br><br>Amazon Bedrock — model invocation, Agents for Bedrock, Knowledge Bases. Amazon Lex v2 — intents, slots, fulfillment Lambda, conversation logs. Lambda, API Gateway, Step Functions, SQS/SNS, Dynamo DB, S3, Cloud Watch. IAM, VPC, Secrets Manager — security and environment best practices. Experience with event-driven and serverless architectures.<br><br>Backend & Engineering<br><br>Python — OOP, async, clean code; REST API design with Fast API or Flask. Containerization: Docker; orchestration experience (ECS / EKS) is a plus. Git, CI/CD pipelines, automated testing, and prompt versioning practices.<br><br>✨ Bonus Points If You Have<br><br>Experience running local LLaMA inference (Ollama, v LLM, Hugging Face Transformers). Exposure to voice bots, STT/TTS pipelines, or multi-modal AI. Knowledge of logistics, e-commerce, or delivery operations domains. Arabic language NLP experience (Snoonu serves Qatar).<br><br>Inside Snoonu’s Universe<br><br>Snoonu is Qatar’s homegrown Super App, reinventing daily life with blazing-fast delivery, shopping, and more – all in one place. Powered by tech, driven by a global team, and obsessed with making life easier.<br><br>The Dream We’re Chasing<br><br>To be the first Qatari Ultra App that propels the region and its community through innovation and technology. We have global ambitions where what we do surpasses norms and limitations every time.<br><br>The Quest We’re On<br><br>To radically transform how people live by leveraging technology to connect them with endless possibilities.<br><br>Our Everyday Superpowers<br><br>???? Be Customer Obsessed: “Focus on the customer and all else will follow.”<br><br>???? Act with Integrity: “We are honest, ethical, and trustworthy in everything we do.”<br><br>???? Be Curious and Creative: “We constantly innovate and create solutions to bring a lasting positive impact.”<br><br>????Lead by Example and Take Ownership: “Be the change you want to see and take ownership.”<br><br>???? Work Smart and Deliver Results: “You can do more by doing less, better, and faster.”<br><br>???????? It's All About People: “Be a team player; together we are stronger.”<br><br>Perks & Worklife Magic At Snoonu<br><br>???? Global Vibes – Collaborate with a worldwide crew.<br><br>???? Brain Boosters – Learning budgets, access to courses, and tools for your growth.<br><br>???? Builder’s Playground – Own your tasks, own your path! We’re big on autonomy.<br><br>????️ Flexible Time Off – We take recharging seriously. Generous leave and wellness policies.<br><br>????️ Agile Everything – Scrum isn’t a buzzword here. It’s how we roll, from product to ops.<br><br>Great Place to Work® Certified<br><br>We’re certified as a Great Place to Work®, a recognition that celebrates a culture we’ve built together where people come first, always. This certification reflects our commitment to creating a workplace where everyone feels valued, empowered, and inspired to do their best work.<br><br>Certified for Excellence<br><br>Our ISO 9001:2015 and ISO 45001:2018 certifications demonstrate our dedication to world-class quality and a safe, supportive workplace, reinforcing our promise to deliver exceptional service while prioritizing the wellbeing of our people.<br><br>Beyond the Code: Giving Back Matters<br><br>We don’t just build apps. We’re committed to doing business sustainably and giving back to the community that fuels us. From eco-conscious practices to CSR projects, we’re always finding ways to do better—and we invite you to be a part of that mission.<br><br>Diversity Isn’t Just a Buzzword<br><br>At Snoonu, fairness and inclusion are the foundation of everything we do. We’re proud to be an equal opportunity workplace that welcomes people from every walk of life. Be bold. Be you. Thrive here.<br><br>Let’s Build the Future Together<br><br>Apply now to join a team where your contributions spark a change and your voice is heard. Let’s make some magic together.<br><br>Stay in the loop—connect with us on Linked In!
Qatar - Doha
???? Welcome to Your Next Adventure!<br><br>We are looking for a Senior AI Engineer to join Snoonu's R&D team as a technical anchor for our conversational AI and agentic automation strategy. You will lead the design and delivery of production-grade chatbot systems powered by AWS and frontier LLMs (Claude-first), and architect Agentic AI pipelines that encode Snoonu's SOPs into autonomous, reliable workflows across customer support, order verification, and logistics. Beyond building, you will set technical standards, guide junior engineers, and act as a key decision-maker in choosing the next technology directions the team will discover and dominate.<br><br>???? What You’ll Get Your Hands On<br><br>Technical Leadership & Architecture<br><br>Own the end-to-end architecture of Snoonu's conversational AI and agentic automation platform — from LLM selection and prompt strategy to cloud infrastructure and observability. Define engineering standards, design patterns, and best practices for AI system development; conduct design reviews and enforce quality bars. Mentor and guide junior/mid-level engineers; review code, provide technical feedback, and accelerate the team's LLM engineering capabilities. Partner directly with the R&D Director to evaluate emerging technologies, shape the team's technical roadmap, and present recommendations with trade-off analysis.<br><br>Conversational AI & Chatbot Development<br><br>Lead the design and delivery of multi-channel chatbots (web, Whats App, app) using AWS Lex, Bedrock, and API Gateway integrated with Claude or other LLMs. Own complex dialogue system challenges: multi-turn reasoning, context persistence, intent disambiguation, and graceful fallback strategies. Integrate chatbots with Snoonu's backend services (order management, CRM, logistics APIs) via secure, scalable RESTful/event-driven patterns. Drive LLM evaluation cycles — benchmark model versions, prompt strategies, and RAG configurations against production quality and cost targets.<br><br>Agentic AI Pipelines<br><br>Architect Agentic AI systems that encode Snoonu SOPs as autonomous, multi-step workflows for customer support, order verification, and logistics operations. Select and govern the right orchestration approach (Lang Graph, Crew AI, Bedrock Agents, Step Functions) per use case — with a clear rationale on reliability, debuggability, and scalability. Design robust memory, context management, tool-use, and guardrail layers to ensure agents behave predictably in adversarial or edge-case conditions. Establish human-in-the-loop checkpoints, confidence thresholds, and escalation paths — ensuring agents augment rather than replace human judgment in critical decisions.<br><br>AWS Infrastructure & MLOps<br><br>Design and own the cloud backbone for AI services: Lambda, ECS/Fargate, SQS/SNS, Dynamo DB, S3, Cloud Watch, and Bedrock — with a focus on scalability, cost, and reliability. Build CI/CD pipelines for prompt versioning, model rollout, A/B testing, and automated evals before production deployment. Define and enforce monitoring standards for drift, latency, cost, and failure rates across all deployed AI systems.<br><br>R&D & Innovation<br><br>Lead frontier model evaluation — benchmark Claude, GPT, LLaMA, Mistral, and emerging open-weight models against Snoonu's specific use cases and constraints. Identify and prototype the next high-leverage AI capability the team should build — bring experiments from idea to validated proof-of-concept with clear go/no-go criteria. Produce high-quality technical documentation: architecture decision records, experimental results, and prompt engineering playbooks for team-wide use.<br><br>????♂️ The Magic You Bring<br><br>Education<br><br>Bachelor's or Master's degree in Computer Science, AI, Software Engineering, or a related field.<br><br>Experience<br><br>5–8 years of hands-on software engineering experience, with at least 3 years focused on LLM-based systems, conversational AI, or agentic architectures. Demonstrated track record of owning and shipping production AI systems end-to-end — not just models, but the full stack from API to monitoring. Portfolio, Git Hub, or detailed case studies required. Prior experience in a senior IC or tech lead role: setting technical direction, conducting design reviews, and mentoring engineers. Strong Python and backend development skills (Fast API / Flask preferred); ability to write clean, production-grade, maintainable code. Research-driven mindset — obsessed with what's next in AI; able to translate frontier research into production value quickly. Extreme ownership: you define the problem, architect the solution, ship it, and hold yourself accountable for outcomes — without waiting to be told. Strong business context awareness — you think about ROI, operational impact, and user outcomes, not just technical elegance. Senior communicator: can explain complex agent design trade-offs to non-engineers, write compelling technical proposals, and influence direction through clarity of thought. Thrives in ambiguity — can operate effectively in fast-paced R&D environments where the problem definition evolves alongside the solution. Natural multiplier: makes the engineers around them better through code reviews, design feedback, and knowledge sharing. Collaborative and direct — comfortable pushing back on requirements and raising risks early, not just executing orders.<br><br>LLMs & Generative AI (Core)<br><br>Deep experience with Anthropic Claude (claude-3 / claude-sonnet / claude-opus) via API and AWS Bedrock — prompt engineering, tool use, and multi-turn reasoning. Familiarity with Open AI GPT models and open-weight models (LLaMA 3, Mistral, Phi) — fine-tuning, quantization, and local inference is a strong plus. Retrieval-Augmented Generation (RAG): vector databases (Open Search, Pinecone, pgvector), embedding models, and hybrid search. Agentic frameworks: Lang Chain / Lang Graph, Crew AI, Auto Gen, or AWS Bedrock Agents. Prompt engineering, system prompt design, evaluation (evals), and red-teaming for production safety.<br><br>AWS Services (Core)<br><br>Amazon Bedrock — model invocation, Agents for Bedrock, Knowledge Bases. Amazon Lex v2 — intents, slots, fulfillment Lambda, conversation logs. Lambda, API Gateway, Step Functions, SQS/SNS, Dynamo DB, S3, Cloud Watch. IAM, VPC, Secrets Manager — security and environment best practices. Experience with event-driven and serverless architectures.<br><br>Backend & Engineering<br><br>Python — OOP, async, clean code; REST API design with Fast API or Flask. Containerization: Docker; orchestration experience (ECS / EKS) is a plus. Git, CI/CD pipelines, automated testing, and prompt versioning practices.<br><br>✨ Bonus Points If You Have<br><br>Experience running local LLaMA inference (Ollama, v LLM, Hugging Face Transformers). Exposure to voice bots, STT/TTS pipelines, or multi-modal AI. Knowledge of logistics, e-commerce, or delivery operations domains. Arabic language NLP experience (Snoonu serves Qatar).<br><br>Inside Snoonu’s Universe<br><br>Snoonu is Qatar’s homegrown Super App, reinventing daily life with blazing-fast delivery, shopping, and more – all in one place. Powered by tech, driven by a global team, and obsessed with making life easier.<br><br>The Dream We’re Chasing<br><br>To be the first Qatari Ultra App that propels the region and its community through innovation and technology. We have global ambitions where what we do surpasses norms and limitations every time.<br><br>The Quest We’re On<br><br>To radically transform how people live by leveraging technology to connect them with endless possibilities.<br><br>Our Everyday Superpowers<br><br>???? Be Customer Obsessed: “Focus on the customer and all else will follow.”<br><br>???? Act with Integrity: “We are honest, ethical, and trustworthy in everything we do.”<br><br>???? Be Curious and Creative: “We constantly innovate and create solutions to bring a lasting positive impact.”<br><br>????Lead by Example and Take Ownership: “Be the change you want to see and take ownership.”<br><br>???? Work Smart and Deliver Results: “You can do more by doing less, better, and faster.”<br><br>???????? It's All About People: “Be a team player; together we are stronger.”<br><br>Perks & Worklife Magic At Snoonu<br><br>???? Global Vibes – Collaborate with a worldwide crew.<br><br>???? Brain Boosters – Learning budgets, access to courses, and tools for your growth.<br><br>???? Builder’s Playground – Own your tasks, own your path! We’re big on autonomy.<br><br>????️ Flexible Time Off – We take recharging seriously. Generous leave and wellness policies.<br><br>????️ Agile Everything – Scrum isn’t a buzzword here. It’s how we roll, from product to ops.<br><br>Great Place to Work® Certified<br><br>We’re certified as a Great Place to Work®, a recognition that celebrates a culture we’ve built together where people come first, always. This certification reflects our commitment to creating a workplace where everyone feels valued, empowered, and inspired to do their best work.<br><br>Certified for Excellence<br><br>Our ISO 9001:2015 and ISO 45001:2018 certifications demonstrate our dedication to world-class quality and a safe, supportive workplace, reinforcing our promise to deliver exceptional service while prioritizing the wellbeing of our people.<br><br>Beyond the Code: Giving Back Matters<br><br>We don’t just build apps. We’re committed to doing business sustainably and giving back to the community that fuels us. From eco-conscious practices to CSR projects, we’re always finding ways to do better—and we invite you to be a part of that mission.<br><br>Diversity Isn’t Just a Buzzword<br><br>At Snoonu, fairness and inclusion are the foundation of everything we do. We’re proud to be an equal opportunity workplace that welcomes people from every walk of life. Be bold. Be you. Thrive here.<br><br>Let’s Build the Future Together<br><br>Apply now to join a team where your contributions spark a change and your voice is heard. Let’s make some magic together.<br><br>Stay in the loop—connect with us on Linked In!
Qatar - Doha
???? Welcome to Your Next Adventure!<br><br>We are looking for a Senior AI Engineer to join Snoonu's R&D team as a technical anchor for our conversational AI and agentic automation strategy. You will lead the design and delivery of production-grade chatbot systems powered by AWS and frontier LLMs (Claude-first), and architect Agentic AI pipelines that encode Snoonu's SOPs into autonomous, reliable workflows across customer support, order verification, and logistics. Beyond building, you will set technical standards, guide junior engineers, and act as a key decision-maker in choosing the next technology directions the team will discover and dominate.<br><br>???? What You’ll Get Your Hands On<br><br>Technical Leadership & Architecture<br><br>Own the end-to-end architecture of Snoonu's conversational AI and agentic automation platform — from LLM selection and prompt strategy to cloud infrastructure and observability. Define engineering standards, design patterns, and best practices for AI system development; conduct design reviews and enforce quality bars. Mentor and guide junior/mid-level engineers; review code, provide technical feedback, and accelerate the team's LLM engineering capabilities. Partner directly with the R&D Director to evaluate emerging technologies, shape the team's technical roadmap, and present recommendations with trade-off analysis.<br><br>Conversational AI & Chatbot Development<br><br>Lead the design and delivery of multi-channel chatbots (web, Whats App, app) using AWS Lex, Bedrock, and API Gateway integrated with Claude or other LLMs. Own complex dialogue system challenges: multi-turn reasoning, context persistence, intent disambiguation, and graceful fallback strategies. Integrate chatbots with Snoonu's backend services (order management, CRM, logistics APIs) via secure, scalable RESTful/event-driven patterns. Drive LLM evaluation cycles — benchmark model versions, prompt strategies, and RAG configurations against production quality and cost targets.<br><br>Agentic AI Pipelines<br><br>Architect Agentic AI systems that encode Snoonu SOPs as autonomous, multi-step workflows for customer support, order verification, and logistics operations. Select and govern the right orchestration approach (Lang Graph, Crew AI, Bedrock Agents, Step Functions) per use case — with a clear rationale on reliability, debuggability, and scalability. Design robust memory, context management, tool-use, and guardrail layers to ensure agents behave predictably in adversarial or edge-case conditions. Establish human-in-the-loop checkpoints, confidence thresholds, and escalation paths — ensuring agents augment rather than replace human judgment in critical decisions.<br><br>AWS Infrastructure & MLOps<br><br>Design and own the cloud backbone for AI services: Lambda, ECS/Fargate, SQS/SNS, Dynamo DB, S3, Cloud Watch, and Bedrock — with a focus on scalability, cost, and reliability. Build CI/CD pipelines for prompt versioning, model rollout, A/B testing, and automated evals before production deployment. Define and enforce monitoring standards for drift, latency, cost, and failure rates across all deployed AI systems.<br><br>R&D & Innovation<br><br>Lead frontier model evaluation — benchmark Claude, GPT, LLaMA, Mistral, and emerging open-weight models against Snoonu's specific use cases and constraints. Identify and prototype the next high-leverage AI capability the team should build — bring experiments from idea to validated proof-of-concept with clear go/no-go criteria. Produce high-quality technical documentation: architecture decision records, experimental results, and prompt engineering playbooks for team-wide use.<br><br>????♂️ The Magic You Bring<br><br>Education<br><br>Bachelor's or Master's degree in Computer Science, AI, Software Engineering, or a related field.<br><br>Experience<br><br>5–8 years of hands-on software engineering experience, with at least 3 years focused on LLM-based systems, conversational AI, or agentic architectures. Demonstrated track record of owning and shipping production AI systems end-to-end — not just models, but the full stack from API to monitoring. Portfolio, Git Hub, or detailed case studies required. Prior experience in a senior IC or tech lead role: setting technical direction, conducting design reviews, and mentoring engineers. Strong Python and backend development skills (Fast API / Flask preferred); ability to write clean, production-grade, maintainable code. Research-driven mindset — obsessed with what's next in AI; able to translate frontier research into production value quickly. Extreme ownership: you define the problem, architect the solution, ship it, and hold yourself accountable for outcomes — without waiting to be told. Strong business context awareness — you think about ROI, operational impact, and user outcomes, not just technical elegance. Senior communicator: can explain complex agent design trade-offs to non-engineers, write compelling technical proposals, and influence direction through clarity of thought. Thrives in ambiguity — can operate effectively in fast-paced R&D environments where the problem definition evolves alongside the solution. Natural multiplier: makes the engineers around them better through code reviews, design feedback, and knowledge sharing. Collaborative and direct — comfortable pushing back on requirements and raising risks early, not just executing orders.<br><br>LLMs & Generative AI (Core)<br><br>Deep experience with Anthropic Claude (claude-3 / claude-sonnet / claude-opus) via API and AWS Bedrock — prompt engineering, tool use, and multi-turn reasoning. Familiarity with Open AI GPT models and open-weight models (LLaMA 3, Mistral, Phi) — fine-tuning, quantization, and local inference is a strong plus. Retrieval-Augmented Generation (RAG): vector databases (Open Search, Pinecone, pgvector), embedding models, and hybrid search. Agentic frameworks: Lang Chain / Lang Graph, Crew AI, Auto Gen, or AWS Bedrock Agents. Prompt engineering, system prompt design, evaluation (evals), and red-teaming for production safety.<br><br>AWS Services (Core)<br><br>Amazon Bedrock — model invocation, Agents for Bedrock, Knowledge Bases. Amazon Lex v2 — intents, slots, fulfillment Lambda, conversation logs. Lambda, API Gateway, Step Functions, SQS/SNS, Dynamo DB, S3, Cloud Watch. IAM, VPC, Secrets Manager — security and environment best practices. Experience with event-driven and serverless architectures.<br><br>Backend & Engineering<br><br>Python — OOP, async, clean code; REST API design with Fast API or Flask. Containerization: Docker; orchestration experience (ECS / EKS) is a plus. Git, CI/CD pipelines, automated testing, and prompt versioning practices.<br><br>✨ Bonus Points If You Have<br><br>Experience running local LLaMA inference (Ollama, v LLM, Hugging Face Transformers). Exposure to voice bots, STT/TTS pipelines, or multi-modal AI. Knowledge of logistics, e-commerce, or delivery operations domains. Arabic language NLP experience (Snoonu serves Qatar).<br><br>Inside Snoonu’s Universe<br><br>Snoonu is Qatar’s homegrown Super App, reinventing daily life with blazing-fast delivery, shopping, and more – all in one place. Powered by tech, driven by a global team, and obsessed with making life easier.<br><br>The Dream We’re Chasing<br><br>To be the first Qatari Ultra App that propels the region and its community through innovation and technology. We have global ambitions where what we do surpasses norms and limitations every time.<br><br>The Quest We’re On<br><br>To radically transform how people live by leveraging technology to connect them with endless possibilities.<br><br>Our Everyday Superpowers<br><br>???? Be Customer Obsessed: “Focus on the customer and all else will follow.”<br><br>???? Act with Integrity: “We are honest, ethical, and trustworthy in everything we do.”<br><br>???? Be Curious and Creative: “We constantly innovate and create solutions to bring a lasting positive impact.”<br><br>????Lead by Example and Take Ownership: “Be the change you want to see and take ownership.”<br><br>???? Work Smart and Deliver Results: “You can do more by doing less, better, and faster.”<br><br>???????? It's All About People: “Be a team player; together we are stronger.”<br><br>Perks & Worklife Magic At Snoonu<br><br>???? Global Vibes – Collaborate with a worldwide crew.<br><br>???? Brain Boosters – Learning budgets, access to courses, and tools for your growth.<br><br>???? Builder’s Playground – Own your tasks, own your path! We’re big on autonomy.<br><br>????️ Flexible Time Off – We take recharging seriously. Generous leave and wellness policies.<br><br>????️ Agile Everything – Scrum isn’t a buzzword here. It’s how we roll, from product to ops.<br><br>Great Place to Work® Certified<br><br>We’re certified as a Great Place to Work®, a recognition that celebrates a culture we’ve built together where people come first, always. This certification reflects our commitment to creating a workplace where everyone feels valued, empowered, and inspired to do their best work.<br><br>Certified for Excellence<br><br>Our ISO 9001:2015 and ISO 45001:2018 certifications demonstrate our dedication to world-class quality and a safe, supportive workplace, reinforcing our promise to deliver exceptional service while prioritizing the wellbeing of our people.<br><br>Beyond the Code: Giving Back Matters<br><br>We don’t just build apps. We’re committed to doing business sustainably and giving back to the community that fuels us. From eco-conscious practices to CSR projects, we’re always finding ways to do better—and we invite you to be a part of that mission.<br><br>Diversity Isn’t Just a Buzzword<br><br>At Snoonu, fairness and inclusion are the foundation of everything we do. We’re proud to be an equal opportunity workplace that welcomes people from every walk of life. Be bold. Be you. Thrive here.<br><br>Let’s Build the Future Together<br><br>Apply now to join a team where your contributions spark a change and your voice is heard. Let’s make some magic together.<br><br>Stay in the loop—connect with us on Linked In!
Qatar National Bank
Qatar
<h2 class="h5">Job description</h2>
<div class="t-break" data-jb-field="description">
Job Summary <br> <p>The Assistant Vice President, Asset Management Middle Office / Performance & Risk Analyst is responsible for calculating, analyzing, and reporting portfolio performance and risk metrics across QNB Asset Management’s investment products. The role includes preparing customized client performance reports, supporting benchmark comparisons, conducting attribution and transaction cost analysis, and maintaining consistency with performance standards such as GIPS. This role collaborates closely with investment teams, product specialists, and compliance to ensure that reporting is accurate, insightful, and aligned with internal and regulatory requirements.</p><br> <br> <br><br> Main Responsibilities <br> <p><strong>A. Shareholder & Financial:</strong></p><br><p>- Calculate portfolio performance and risk across asset classes and benchmark against strategic targets</p><br><p>- Conduct performance & risk attribution analysis, identifying contributions from asset allocation, security selection, currency, and style factors</p><br><p>- Build customized reports based on client requirements</p><br><p>- Generate and interpret risk-adjusted return metrics (e.g., Sharpe ratio, alpha, beta, tracking error, volatility)</p><br><p>- Analyze fund expenses, transaction costs, and fees to support transparency and cost benchmarking</p><br><p>- Collaborate with investment managers to optimize fund structures based on historical performance trends</p><br><p>- Maintain and improve performance measurement tools, templates, and data pipelines</p><br><p>- Prepare composite performance summaries in compliance with GIPS reporting standards</p><br><p>- Contribute to automation and quality control for recurring client and internal reports</p><br><p>- Implements KPI’s and best practices for Assistant Vice President, Asset Management Middle Office</p><br><p>- Promote cost consciousness and efficiency and enhance productivity, to minimise cost, avoid waste, and optimise benefits for the bank.</p><br><p>- Act within the limits of the powers delegated to the incumbent.</p><br><p><strong>B. Customer (Internal & External):</strong></p><br><p>- Maintain up-to-date knowledge of performance attribution models, risk metrics, and fund structures</p><br><p>- Continuously develop reporting skills using advanced Excel, SQL, VBA, and BI tools</p><br><p>- Participate in internal workshops and cross-functional sessions with Product, Investment, and Business Control teams</p><br><p>- Support the team in adopting automation tools and improving dashboard visualizations</p><br><p>- To assist customers in all their queries on Bank’s product and seek solution to their requests.</p><br><p>- Maintain activities in accordance with Service Level Agreements (SLAs) with internal departments/units to achieve improvements in turn-around time.</p><br><p>- Build and maintain strong/effective relationships with related departments/units to achieve the Group’s objectives.</p><br><p>- Provide timely/accurate data to external/internal Auditors, Compliance, Financial Control and Risk when required.</p><br><p><strong>C. Internal (Processes, Products, Regulatory):</strong></p><br><p>- Collaborate with Investment Management and Product to ensure accurate, relevant reporting</p><br><p>- Work closely with Trade Support & Data, and Business Control to ensure data inputs meet regulatory and internal guidelines</p><br><p>- Proactively flag data discrepancies, outliers, or reporting exceptions</p><br><p><strong>D. Learning & Knowledge:</strong></p><br><p>- Proactively identify areas for professional development of self and undertake development activities.</p><br><p>- Seek out opportunities to remain current with all developments in professional field.</p><br><p><strong>E. Legal, Regulatory, and Risk Framework Responsibilities:</strong></p><br><p>- Comply with all applicable legal, regulatory and internal compliance requirements including, but not limited to, Group Compliance Policies and Procedures (AML & CTF, Sanctions Policy, Data Protection Policy, Fraud Control Policy, Whistle Blowing Policy, Conflict of Interest and Insider Dealing Policy).</p><br><p>- Understand and effectively perform your role under the Three Lines of Defense principle to identify measure, monitor, manage and report risks.</p><br><p>- Ensure systematic good outcomes for clients in accordance with Conduct Risk policy.</p><br><p>- Support the framework of RCSA, KRI, Incident reporting and remediation, as appropriate, in accordance with the Operational Risk Management requirements.</p><br><p>- Maintain appropriate knowledge to ensure full qualification to undertake the role.</p><br><p>- Complete all mandatory training provided by the Bank, attain, and maintain the required levels of competence.</p><br><p>- Attend mandatory (internal and external) seminars as instructed by the Bank.</p><br><p><strong>F. Other:</strong></p><br><p>- Ensure high standards of data protection and confidentiality to safeguard commercially sensitive information.</p><br><p>- Maintaining utmost confidentiality concerning customer and internal bank information obtained during the course of business and provide such information on a need-to-know basis only to Senior Management of QNB, Audit and Compliance functions, and relevant Regulators.</p><br><p>- Maintain high professional standards to uphold QNB's reputation and to strengthen its market leadership position.</p><br><p>- All other ad hoc duties/activities related to QNB that management might request from time to time.</p><br> <br> <br><br> Education and Experience Requirements <br> <p>- Bachelor’s degree in Finance, Mathematics, Economics, or related quantitative field</p><br><p>- CFA Level I or CIPM (Certificate in Investment Performance Measurement) preferred</p><br><p>- Minimum of 10 years of experience in performance analysis, risk attribution, or investment operations in asset management or financial services</p><br><p>- Proficiency in performance measurement tools, GIPS reporting frameworks, and attribution methodologies</p><br><p>- Hands-on experience with Excel, Python, SQL, or BI tools (e.g., Power BI, Tableau)</p><br><p>- Deep understanding of performance attribution, benchmark alignment, and client reporting</p><br><p>- Knowledge of risk-adjusted return metrics and investment mandates</p><br><p>- Ability to translate complex data into clear client-facing insights</p><br><p>- Excellent oral and written communication skills (including report writing) in English and Arabic.</p><br><p>- Good interpersonal and presentation skills.</p><br><p>- Understanding of the relevant laws, regulations, and practices.</p><br><p>- Ability to make decisions and follow through with initiatives.</p><br><p>- Personal integrity and self-management.</p><br><p>- Planning, organizing, and analytical ability.</p><br><p>- Results oriented.</p><br><p>- Strong analytical skills and the ability to communicate both verbally and in writing with all levels of management.</p><br> <br> <br> </div>
Qatar - Doha
Location: Doha, Qatar (On-site) Duration: 12 Months (Extendable)<br>Description<br>Please apply only if you are open to relocating and working onsite in Doha, Qatar for a minimum of 12 months. Candidates already in Qatar with a valid work permit are encouraged to apply.<br>We are hiring a Cards Analytics Specialist to work on a project for one of our clients, a leading regional bank. This is a specialist analytics role sitting inside the Cards & Payments function, and it calls for someone who has spent the bulk of their career working specifically on card portfolios, not general banking analytics.<br>You will own how card portfolio performance is measured, understood, and acted upon. The remit runs the full length of the card lifecycle, from how cards are acquired and activated through to spend, retention, and profitability. We are looking for someone who does not stop at producing numbers but interprets them, spots what is moving and why, and puts clear recommendations in front of senior stakeholders.<br>This is a hands-on individual contributor role with real visibility. Minimum 7 years of experience is required, and that experience needs to be rooted in cards.<br>The work itself<br>Recurring card portfolio reporting is the backbone of the role. You will build and run the dashboards and performance packs that leadership relies on across daily, weekly, and monthly cycles, tracking acquisition, activation, spend, delinquency, attrition, and profitability across the card book.<br>From there, the work becomes investigative. You will pull card portfolios apart by product, channel, customer cohort, and vintage to work out what is driving performance and where the risks and opportunities sit.<br>Card campaign measurement is a major part of the mandate. When the bank runs a card marketing or engagement campaign, you are the person who proves whether it worked, using proper test-versus-control comparisons, return-on-spend calculations, and response-rate analysis, and who says what should change next time.<br>You will also act as the analytics partner to the Cards Product, Portfolio, Marketing, and Risk teams, turning analysis into briefing packs, business cases, and what-if scenarios that feed straight into decisions. A key part of this is keeping metric definitions consistent across teams, so everyone is working from the same numbers and the same understanding of what each one means.<br>Finally, you will keep pushing the reporting operation forward, cutting out manual effort, tightening data quality, and giving business users more ability to answer their own questions.<br>What you need to have Mandatory:<br>Minimum 7 years working in cards analytics, card portfolio analytics, or business intelligence within banking, payments, or financial services, with a clear majority of that time spent on cards specifically Proven hands-on work analysing a live card portfolio, whether credit, debit, or both Strong SQL, comfortable writing complex queries against large datasets without support Advanced Excel, including pivot tables, lookup and match functions, and data modelling Working proficiency in Tableau, Power BI, or a comparable visualisation tool Professional working proficiency in English Available immediately or on a notice period of up to 30 days<br>Preferred:<br>Python or R for statistical work, data manipulation, and automation SAS for portfolio analysis and data extraction Exposure to CRM or campaign management platforms Familiarity with core banking or card management system data A working grasp of how a card portfolio actually makes money, across the main revenue and cost levers A relevant analytics certification<br>The kind of thinking we want<br>You should be fluent in how card portfolios behave: how customers move from acquisition to activation to steady usage, what makes them fall dormant or attrite, and what drives the balances and revenue they generate along the way. You should understand delinquency and attrition not just as metrics but as signals worth investigating. You should also know how card campaigns are targeted, segmented, and measured, and how to isolate genuine uplift from noise. Just as important as the technical skill is the instinct to keep asking why, and the ability to explain a complex finding to a non-technical senior audience in plain commercial terms.<br>What success looks like<br>Reporting that lands on time and is trusted to be accurate Dashboards that stakeholders genuinely use to answer their own questions Card campaigns measured end to end, promptly after they close, with a clear read on what worked Recommendations that get acted on, not just filed A steadily shrinking pile of manual reporting as automation takes over
Ernst & Young AE
Qatar - Qatar
<section><p class="heading jdMain">Job Description</p><p class="heading">Roles & Responsibilities</p><div class="paragraph"><p>As part of the Financial Services Risk Management (FSRM) practice you will provide a well-integrated broad array of risk management services to capital market participants, such as, Banks, Pension Funds, Investment Companies and Insurance. FSRM products and services include all aspects related to Pillar one and Pillar Two Risks, Risk Analytics, Credit Analysis, Investment Analysis and Risk Reporting.</p><p>As an FSRM Manager, you'll technically contribute to manage and lead FS Risk Management engagements. You will work effectively as a team leader having the responsibility, providing support, maintaining communication, and updating engagement directors and partners on progress. You'll also build valuable relationships with external clients and internal peers. In addition, you'll contribute to presentations and provide inputs to proposals.</p><p>Drawing on your skills and experience, you'll stay abreast of innovative commercial insights for clients. You ll also assist in packaging overall project findings into clear, concise, high-quality products.</p><p>You'll serve as a role model to junior team members for quality & risk management and ensure that junior team members are aware and understand and comply with EY's Quality & Risk Management guidelines. As a Manager, you'll also communicate effectively with junior team members and help cultivating them to becoming a high performer.</p></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><ul><li>Strong analytical and problem-solving skills</li><li>Strong drive to excel professionally, and to guide and motivate others</li><li>Advanced written and verbal communication skills</li><li>Dedicated, innovative, resourceful, analytical and able to work under pressure</li><li>Foster an efficient, innovative and team-oriented work environment</li><li>Strong educational background from a top institution, quantitative/ finance/ economics/ actuarial programme</li><li>Min. 7 years of relevant professional experience in a consulting and /or banking environment.</li><li>Experience in working in a project-based, team-oriented environment, ideally in the banking sector or consulting, with a proven track record of managing teams and delivering in fast-paced and demanding environments</li><li>Experience and proficiency in programming languages: R, Paython or SQL.</li><li>Excellent analytical, report-writing, facilitation and presentation skills</li><li>Strong management skills and proven people management skills</li><li>Experience in managing both internal and external stakeholders</li><li>Ability and appetite to drive business development and contribute to the growth of EY s solutions</li><li>Professional certifications: FRM and/or CFA</li><li>Highly motivated individuals with excellent problem-solving skills and the ability to prioritize shifting workloads in a rapidly changing industry. An effective communicator, you ll be a confident leader equipped with strong people management skills and a genuine passion to make things happen in a dynamic organization. If you re ready to take on a wide range of responsibilities, and are committed to seeking out new ways to make a difference, this role is for you.</li></ul><p></p></section>