Jobs For Faculty Of Science Graduates in Qatar

:نبذة عن المعهد<br><br>تأسس معهد الدوحة للدراسات العليا في قطر في عام 2015 كمؤسسة مستقلة للدراسات العليا، ومقره الدوحة. يقدّم المعهد برامج الماجستير والدكتوراه في كليتين: كلية العلوم الاجتماعية والإنسانية، وكلية الاقتصاد والإدارة والسياسات العامة، معتمدًا اللغة العربية كلغة أساس للدراسة والبحث، مع اشتراط اتقان الإنجليزية. يعمل المعهد على تأهيل باحثين قادرين على الإسهام في إنتاج المعرفة وفق المعايير العالميّة، ومهنيين متمكّنين في المهارات المتقدمة في تخصصاتهم، وقياديين قادرين على الاستجابة لحاجات العالم العربي في التنمية المستدامة، والنهوض الفكري والاجتماعي. يتبنى المعهد تكامل التعليم والتعلّم مع البحث العلمي، مع مراعاة تكامل التخصصات ومحورية الطلاب في العملية التعليمية، ويوفر لمنتسبيه الحرية الأكاديمية، مع التأكيد على قيم النزاهة والمهنية.<br><br>:نبذة عن البرنامج<br><br>يهدف برنامج العلوم السياسية والعلاقات الدولية، أحد برامج كلية العلوم الاجتماعية والإنسانية بمعهد الدوحة للدراسات العليا، إلى تكوين جيل جديد من المتخصصين العرب في العلوم السياسية قادرين على إنتاج معرفة معبرة عن المنطقة ومنها ولأجلها، والانخراط في حوار نقدي مباشر مع النقاشات النظرية والمقاربات المنهجية في هذا الحقل المعرفي عالميًا. لا يقتصر نهج البرنامج مع طرق التدريس في الجامعات العالمية المرموقة فحسب، بل يشمل أيضًا بُعدًا مميزًا يضم الإسهامات والمضامين والاهتمامات العربية. يجسد نهج البرنامج في التدريس والتعلم هدف معهد الدوحة للدراسات العليا المتمثل في دمج البحث في التعليم والتعلم. ولتحقيق ذلك يعمل البرنامج على استقطاب أساتذة متمكنين لهم خبرة في التدريس وفي البحث العلمي والنشر في كبريات الدوريات الدولية المتخصصة. إذ يتوقع من أعضاء هيئة التدريس في البرنامج تقديم مساهمات فعالة وأبحاث علمية رفيعة المستوى، والحرص على نقل خبراتهم ومهاراتهم البحثية إلى الطلبة، وتعزيز التعاون العلمي مع زملائهم داخل المعهد وخارجه، بما يسهم في إثراء المعرفة وتطوير الحقل العلمي. كما يتوقع منهم المشاركة في مراجعة نقدية مستمرة للعلوم السياسية والعلاقات الدولية والنظريات السائدة فيها، وهو توجه يشجعه البرنامج في إطار سعيه إلى تقديم إسهامات علمية أصيلة ومبتكرة. ويولي البرنامج اهتمامًا خاصًا برصد ومعالجة أوجه القصور المعرفية في الأدبيات، لا سيما تلك المتعلقة بدراسة القضايا السياسية في المنطقة العربية.<br><br>:موجز عن الشاغر الوظيفي/ الغرض من الوظيفة<br><br>يهدف برنامج العلوم السياسية والعلاقات الدولية إلى استقطاب عضو هيئة تدريس بدوام كامل في تخصص العلاقات الدولية، بما ينسجم مع رسالة معهد الدوحة للدراسات العليا القائمة على التميز الأكاديمي والإنتاج المعرفي وربط البحث العلمي بقضايا السياسات العامة في السياقات الإقليمية والدولية<br><br>على أن يبدأ التعاقد في أغسطس/سبتمبر 2027<br><br>ينبغي أن ت/يكون المرشح/ة متخصص/ة في العلاقات الدولية<br><br>ومن المتوقع أن ت/يساهم المرشح/ة في تدريس مقررات متقدمة على مستوى الدراسات العليا في مجال العلاقات الدولية، إلى جانب الإشراف الأكاديمي على رسائل الماجستير والدكتوراه، ودعم تطوير البيئة البحثية للبرنامج. كما يُنتظر منه/ا المشاركة الفاعلة في اللجان الأكاديمية والإدارية، لا سيما ما يتعلق بعمليات القبول وتطوير البرامج، فضلاً عن الإسهام في إنتاج بحث علمي رصين ونشره في مجلات محكّمة دولياً، بما يعزز مكانة البرنامج ويواكب أولويات المعهد في البحث النقدي متعدد التخصصات وخدمة قضايا المنطقة<br><br>:المهام الرئيسية<br><br> تدريس مقررات على مستوى الدراسات العليا. الإشراف على طلاب الماجستير والدكتوراه في البرنامج والمشاركة الكاملة في الحياة الأكاديمية لمعهد الدوحة للدراسات العليا.نشر الأبحاث في حقول الاختصاص والمجالات المتصلة في الدوريات المحكمة الرائدة في المجال و/ أو دور نشر أكاديمية مرموقة.الاضطلاع بمهام إدارية وخدمة البرنامج والكلية والمعهد والمجتمعالمشاركة في لجان البرنامج والكلية والمعهد. <br><br>المؤهلات والخبرات والمهارات:<br><br>على المتقدمين/ات أن يكونوا<br><br> حاصلين على شهادة الدكتوراه في تخصص العلوم السياسيةذوي سجل بحث ونشر علمي في ميادين الاختصاص والمجالات المتصلة في مجلات محكمة عالميًا تتناسب مع رتبتهم العلمية.ذوي كفاءة وخبرة في التدريس الجامعي لمرحلة الدراسات العليا.متقنين للغة العربية.قادرين على جذب الدعم الخارجي والتمويل البحثي.مستعدين للمشاركة في البحوث التشاركية متعددة التخصصات مع أعضاء آخرين في البرنامج و/أو المعهد.قادرين على بناء سمعة دولية في مجالات البحث المتخصصة.<br><br>المتطلبات:<br><br>سيرة ذاتية مفصلة.نسخة من شهادة الدكتوراه.خطاب يشرح الحافز على التقدم للشاغر الوظيفي. خطاب يشرح فلسفة التعليم والإشراف.<br><br>مرفقات تثبت الخبرة التدريسية (مثل وصف المقررات وتقييم الطلاب للمقرر) إذا كان المرشح يشغل وظيفة تدريس. <br><br>نسخ من الأبحاث المنشورة أو الأبحاث قيد الإعداد.خطاب يشرح الإنجازات البحثية للمتقدم أو المتقدمة و/ أو المخطط البحثي الحالي.أسماء ومعلومات التواصل لثلاثة معرفين لتوفير خطابات مرجعية وتوصيات.قد يتم طلب مواد إضافية في مرحلة لاحقة.<br><br>ملاحظات إضافية:<br><br> يلتزم المعهد بتوفير فرص متساوية في التوظيف.يشجع المعهد الباحثات الإناث على التقدم لشغل الوظائف.سيتم مراجعة طلبات التقديم والنظر فيها فور استلامها إلى حين ملء الشواغر المتاحة. يُرجى إرفاق جميع الوثائق المطلوبة للتقديم عبر صفحة الوظائف على موقع المعهد. ولمزيد من المعلومات والتفاصيل عن معهد الدوحة للدراسات العليا، يُرجى زيارة الموقع www.dohainstitute.edu.qa.<br><br>يُرجى التواصل مع الدكتور عمار الشمايلة على ammar.shamaileh@dohainstitute.edu.qa<br><br>في حال وجود أي تساؤلات أخرى عن الشاغر الوظيفي.<br><br>سيتم التواصل مع مرشحي القائمة القصيرة فقط<br><br>آجال التقديم:<br><br>يغلق في نهاية يوم العمل بتاريخ 01-Nov-26

Job Description<br><br> OCI Data Science Platform: Build, train, evaluate and deploy machine learning models using OCI Data Science, notebooks and Python-based ML solutions. Data Preparation & Feature Engineering: Perform data cleansing, feature engineering, dataset management and model validation activities. Machine Learning & Analytics: Develop supervised and unsupervised models including forecasting, classification, clustering and recommendation solutions. Model Lifecycle & Governance: Manage model lifecycle, versioning, approvals, governance and traceability through OCI Model Catalog or equivalent controls. MLOps & Deployment: Deploy models as scalable REST API endpoints and support CI/CD pipelines for model promotion and production deployment. Monitoring & Continuous Improvement: Monitor model performance, utilisation and drift and support retraining and optimisation activities. Operational Support: Provide L2/L3 support for deployed AI/ML solutions, troubleshooting, enhancements and knowledge base updates.<br><br>Responsibilities<br><br>Primary Skills:<br><br> OCI Data Science Python SQL Machine Learning Model Validation Statistical Analysis<br><br>Secondary/ Support Skills<br><br> OCI Dev Ops Docker Kubernetes Data Engineering concepts AI Governance Model monitoring<br><br>Tools/ Platforms<br><br> Jupyter Notebooks Tensor Flow PyTorch Scikit-learn OCI Object Storage Oracle Autonomous Database<br><br>Qualifications<br><br> Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Engineering or a related field. Minimum 5 years of experience in data science, machine learning, advanced analytics or predictive modelling. Minimum 3 years of experience using OCI Data Science or equivalent cloud ML platforms. Experience developing, training, deploying and monitoring machine learning models in production environments. Strong understanding of MLOps, feature engineering, model governance and large-scale data analysis. OCI Data Science Professional, OCI AI Foundations Associate or OCI AI Professional certifications are preferred.<br><br>About Malomatia<br><br> ABOUT US <br><br>malomatia is a leading Qatar-based IT services and solutions provider, bringing together top Qatari and international talent to deliver innovative, end-to-end technology solutions that empower clients to achieve their strategic goals.<br><br>Our mission<br><br>Empowering Qatar’s businesses and governments to leap into the digital future with agile, knowledge-driven solutions.<br><br>Our vision<br><br>To become Qatar’s trusted knowledge partner in digital transformation, disrupting industries, shaping the future, and building a world-class tech ecosystem.<br><br>Driving change that makes a real impact<br><br>Since 2008, malomatia has been driving Qatar’s digital transformation through innovative, ISO-certified IT solutions. With expertise across key public and private sectors, we empower the nation’s vision with advanced services in cloud, cybersecurity, AI, and contact center excellence, elevating the role of technology in shaping Qatar’s sustainable future.<br><br>About The Team<br><br>Established in 2008, malomatia is a Qatari leader in IT services and digital transformation. We serve key sectors including Government, Healthcare, Education, Customs, and Transportation, delivering impactful solutions that support national development goals. Powered by a diverse team of skilled Qatari and international IT professionals, we deliver innovative, high-value digital solutions tailored to the unique needs of our clients.<br><br>Our mission is to inspire customers to thrive through digital excellence, and we envision becoming the trusted partner of choice in building a smarter society through technology and talent. We are driven by core values that define our culture and approach: ownership, integrity, empathy, teamwork, transparency, agility, excellence, trust, and innovation.<br><br>Join us in shaping the future of technology in Qatar

We Are<br><br>Our AI & Data team helps clients transform business challenges into opportunities through advanced analytics, AI, and intelligent decision-making. We work across industries to design and deliver practical analytical solutions.<br><br>The Work<br><br>As an AI Decision Science Consultant, you will work with clients to develop analytical solutions, generate insights, and support AI-driven transformation initiatives.<br><br><br>Conducting data analysis and statistical modeling<br>Building predictive and analytical solutions<br>Supporting machine learning use cases and AI initiatives<br>Creating dashboards, reports, and decision-support tools<br>Gathering and documenting client requirements<br>Presenting findings and recommendations to stakeholders<br>Collaborating with multidisciplinary consulting teams<br><br><br>Here's What You Need<br><br><br>Bachelor's degree in Data Science, Statistics, Mathematics, Engineering, Economics, or related field<br>3+ years of analytics, AI, or data science experience<br>Strong analytical and problem-solving skills<br>Experience with SQL, Python, or similar analytical tools<br>Excellent communication and presentation skills<br><br><br>Bonus Points If You Have<br><br><br>Machine learning project experience<br>Data visualization expertise<br>Experience in consulting or client-facing environments

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 Associate, Data Science plays a foundational role in supporting data science initiatives across the bank. The role involves working under the guidance of senior team members to build and deploy machine learning models, conduct exploratory data analysis, and generate data-driven insights to solve business problems. The associate collaborates with business units to understand requirements, supports model development, and contributes to building scalable data science assets that align with QNB’s strategic goals.<br><br>Main Responsibilities<br><br> Shareholder & Financial: - Support the development and tracking of KPIs to measure impact of data science initiatives. - Assist in delivering data analytics solutions that drive business efficiency and revenue growth. - Take part in the overall QNB Data & Analytics strategy execution. - 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): - Work with internal stakeholders to understand business needs and translate them into data problems. - Assist in preparing clear, concise, and insightful reports or dashboards for business users. - Support model testing and deployment activities, ensuring stakeholder alignment and timely delivery. - Ensure activities are conducted in accordance with Service Level Agreements (SLAs) with internal departments and units to achieve significant improvements in turnaround times. - Provide precise and timely data to external and internal auditors, compliance teams, financial control, and risk management when required. - 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): - Support the AVP and other senior data scientists in developing machine learning and statistical models. - Prepare and clean large datasets for analysis and modelling purposes. - Contribute to the implementation of AI/ML pipelines and production-ready solutions. - Document methodologies, outcomes, and learnings for reproducibility and scaling. - 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. Learning & Knowledge: - Stay updated on the latest trends in machine learning, AI, and analytics tools. - Participate in training programs and learning sessions to build advanced analytics capability. - Proactively seek feedback and mentorship from senior team members. - Seek out opportunities to stay current with advancements in 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.<br><br>Education And Experience Requirements<br><br> Bachler Degree University in data science, Computer Science, Mathematics, Engineering, or a related field. Familiarity with machine learning techniques, data wrangling, and model evaluation practices. High Level knowledge in data science tools like Python, R and Jupiter notebooks is desirable.<br><br>Note: you will be required to attach the following:<br><br>Resume/CVCopy of Passport or QID Copy of Education Certificate Copy of Birth Certificate

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p><b>We Are</b></p><br><br><p>Accenture's AI &amp; Data practice helps organizations harness the power of data, analytics, and artificial intelligence to drive competitive advantage and business transformation. We combine industry knowledge, advanced analytics, and scalable technology delivery.</p><br><br><br><p><b>The Work</b></p><br><br><p>As an AI Decision Science Manager, you will lead analytics and AI transformation initiatives while helping organizations make intelligent, data-driven decisions.</p><br><br><ul><li>Leading AI, machine learning, and analytics programs</li><li>Developing decision science and predictive analytics solutions</li><li>Working with clients to define business challenges and opportunities</li><li>Translating business requirements into AI-driven insights</li><li>Leading teams of data scientists and analytics professionals</li><li>Supporting business development and solution creation</li><li>Presenting insights and recommendations to executive stakeholders</li></ul><br> </div>

We Are<br><br>Accenture's AI & Data practice helps organizations harness the power of data, analytics, and artificial intelligence to drive competitive advantage and business transformation. We combine industry knowledge, advanced analytics, and scalable technology delivery.<br><br>The Work<br><br>As an AI Decision Science Manager, you will lead analytics and AI transformation initiatives while helping organizations make intelligent, data-driven decisions.<br><br><br>Leading AI, machine learning, and analytics programs<br>Developing decision science and predictive analytics solutions<br>Working with clients to define business challenges and opportunities<br>Translating business requirements into AI-driven insights<br>Leading teams of data scientists and analytics professionals<br>Supporting business development and solution creation<br>Presenting insights and recommendations to executive stakeholders<br><br><br>Here's What You Need<br><br><br>Bachelor's degree in a quantitative field<br>7+ years of experience in analytics, AI, machine learning, or consulting<br>Experience delivering data-driven transformation programs<br>Strong stakeholder and project management skills<br>Experience with modern analytics platforms and methodologies<br><br><br>Bonus Points If You Have<br><br><br>Master's degree in Data Science, Statistics, AI, or related field<br>Experience with cloud-based AI solutions<br>Experience managing global delivery teams

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> Job Summary <br> <p>The Associate, Data Science plays a foundational role in supporting data science initiatives across the bank. The role involves working under the guidance of senior team members to build and deploy machine learning models, conduct exploratory data analysis, and generate data-driven insights to solve business problems. The associate collaborates with business units to understand requirements, supports model development, and contributes to building scalable data science assets that align with QNB’s strategic goals.</p><br> <br> <br><br> Main Responsibilities <br> <p>A. Shareholder &amp; Financial: - Support the development and tracking of KPIs to measure impact of data science initiatives. - Assist in delivering data analytics solutions that drive business efficiency and revenue growth. - Take part in the overall QNB Data &amp; Analytics strategy execution. - 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. </p><br><p>B. Customer (Internal &amp; External): - Work with internal stakeholders to understand business needs and translate them into data problems. - Assist in preparing clear, concise, and insightful reports or dashboards for business users. - Support model testing and deployment activities, ensuring stakeholder alignment and timely delivery. - Ensure activities are conducted in accordance with Service Level Agreements (SLAs) with internal departments and units to achieve significant improvements in turnaround times. - Provide precise and timely data to external and internal auditors, compliance teams, financial control, and risk management when required. - 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. </p><br><p>C. Internal (Processes, Products, Regulatory): - Support the AVP and other senior data scientists in developing machine learning and statistical models. - Prepare and clean large datasets for analysis and modelling purposes. - Contribute to the implementation of AI/ML pipelines and production-ready solutions. - Document methodologies, outcomes, and learnings for reproducibility and scaling. - 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. </p><br><p>D. Learning &amp; Knowledge: - Stay updated on the latest trends in machine learning, AI, and analytics tools. - Participate in training programs and learning sessions to build advanced analytics capability. - Proactively seek feedback and mentorship from senior team members. - Seek out opportunities to stay current with advancements in 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.</p><br> <br> <br><br> Education and Experience Requirements <br> <p>- Bachler Degree University in data science, Computer Science, Mathematics, Engineering, or a related field. </p><br><p>- Familiarity with machine learning techniques, data wrangling, and model evaluation practices. </p><br><p>- High Level knowledge in data science tools like Python, R and Jupiter notebooks is desirable.</p><br> <br> <br> </div>

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

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

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

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

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p><b>We Are</b></p><br><br><p>Our AI &amp; Data team helps clients transform business challenges into opportunities through advanced analytics, AI, and intelligent decision-making. We work across industries to design and deliver practical analytical solutions.</p><br><br><br><p><b>The Work</b></p><br><br><p>As an AI Decision Science Consultant, you will work with clients to develop analytical solutions, generate insights, and support AI-driven transformation initiatives.</p><br><br><ul><li>Conducting data analysis and statistical modeling</li><li>Building predictive and analytical solutions</li><li>Supporting machine learning use cases and AI initiatives</li><li>Creating dashboards, reports, and decision-support tools</li><li>Gathering and documenting client requirements</li><li>Presenting findings and recommendations to stakeholders</li><li>Collaborating with multidisciplinary consulting teams</li></ul><br> </div>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>We are looking for an experienced IT Data &amp; AI Specialist to design, develop, and maintain data engineering and AI solutions that support business operations and digital transformation initiatives.</p><p>Key Responsibilities</p><ul><li>Design, develop, and maintain scalable data pipelines and data platforms.</li><li>Collect, clean, and transform structured and unstructured data.</li><li>Build, train, test, and deploy Machine Learning and Generative AI models.</li><li>Develop dashboards, reports, and actionable business insights.</li><li>Integrate AI solutions with enterprise applications.</li><li>Ensure data quality, governance, security, and compliance.</li><li>Monitor and optimize data pipelines and AI model performance.</li><li>Collaborate with business and technical stakeholders to deliver data-driven solutions.</li><li>Document data models, pipelines, and AI implementations.</li></ul><p>Required Skills</p><ul><li>Data Analysis</li><li>Data Engineering</li><li>Generative AI</li><li>Python</li><li>SQL</li><li>Machine Learning</li><li>AWS / Azure / GCP</li><li>Data Pipelines</li><li>Data Warehousing</li><li>ETL</li><li>Data Visualization / BI Tools</li><li>Cloud Computing</li></ul><p>Preferred Skills</p><ul><li>Microsoft Copilot</li><li>Google Gemini Enterprise</li><li>Large Language Models (LLMs)</li><li>Prompt Engineering</li><li>AI Solution Integration</li></ul></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"><b>Qualifications</b></p><ul><li>Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field.</li><li>36 years of experience in Data Engineering, Data Analytics, AI, or Machine Learning.</li><li>Strong hands-on experience with Python and SQL.</li><li>Experience with Machine Learning frameworks.</li><li>Experience working with AWS, Azure, or GCP cloud platforms.</li><li>Strong analytical, communication, and problem-solving skills.</li></ul><b>Location Preference:</b><ul><li>Candidates willing to relocate to Qatar.</li></ul><p></p></section>

About Us:Ooredoo is a dynamic global Telecommunications player operating in 10 countries serving more than 138 million customers. Ooredoo Qatar employs approximately 1,600 people driving Ooredoo to be the number one choice for world-class communications services in Qatar, and it is a team that you can be part of!<br>About the Role:This role is responsible for strengthening the AI practice by working closely with the relevant stakeholders (B2B/C, Technology, Finance etc.) on impactful AI/ML and Gen AI use cases to contribute to business strategy, digital growth and an evolving data & AI roadmap. The role will focus on translating customer and commercial needs into scalable ML/Gen AI/Data Science models and decisioning capabilities across business domains including customer value management (CVM), marketing, digital sales and customer care.<br>Functional Context:Ooredoo places strong emphasis on a data-driven culture. In an ever-changing business landscape, there is increasing organizational focus on using AI/ML in day-to-day practice to create value, efficiency, and diversification.<br>The AI Hub division is responsible for putting in place and executing the data & AI roadmap, business plan, and strategy. Ooredoo is building cloud platform-based solutions involving GCP that hosts the data platform and supports analytics and ML workloads, while Azure hosts Gen AI and agentic AI workloads.<br>Role Accountabilities:• Understand business requirements for Telecom business (B2C/B2B) and develop AI/ML based data science models to do value addition.• Own end-to-end AI/ML model lifecycle: problem framing, data discovery, feature engineering, training, validation, deployment, monitoring, and continuous improvement (self-learning where applicable).• Deliver Customer Value Management (CVM) use cases such as churn prediction and prevention, customer lifetime value (CLV), propensity models for upsell/cross-sell, and Next Best Offer / Next Best Action frameworks.• Enable hyper-personalization and real-time decisioning by designing decision logic, recommendation models and event-driven scoring to support always-on campaigns and contextual offers.• Support AI-enabled marketing and digital sales optimization, including audience segmentation, campaign optimization, attribution/uplift measurement, personalized messaging, and digital funnel conversion analytics.• Develop call-center efficiency use cases including call volume forecasting, workforce optimization inputs, routing/prioritization analytics, and AI-assisted service journeys.• Design and implement conversational AI and Gen AI solutions (e.g., virtual assistants, agent-assist, summarization, knowledge retrieval) to improve customer experience and operational efficiency while adhering to governance controls.• Command on PL/SQL with feature extraction, pre-processing of data, training, scoring, and actionable insight extraction in leading database platforms e.g., Teradata, Oracle etc.• Build insights through statistical measures/algorithms/graphs/info graphics and communicate results in a business friendly format for stakeholders and leadership.• Evaluate models and establish robust tracking mechanisms for adoption and realized business outcomes; proactively follow up on lead utilization with use case owners.• Ensure Responsible AI practices: model governance, documentation, privacy-by-design, bias/robustness testing, explainability where required, and secure handling of customer data.• Manage and continuously improve the Data Science Operational Framework, including standards for reusable code, model registries, versioning, and release management in collaboration with Technology teams.• Work as part of a shared function across organization on use cases to support product growth, cost optimization, customer engagement and customer experience improvements.<br>Minimum Entry Qualifications:Bachelor’s Degree in Computer Science, Engineering or Similar<br>Minimum Experience, Essential Knowledge & Skills:10 years' experience in a similar role. Prior experience in data science and AI/ML-based advanced analytics, including hands-on development on leading data science platforms (Dataiku as the primary platform) using Python and R. Demonstrated expertise in predictive modelling for telecommunications (telco) customer analytics (e.g., churn prediction, propensity, customer lifetime value (CLV)) as well as segmentation,recommendation/decisioning systems, and timeseries forecasting. Experience implementing hyper-personalization and Next Best Offer/Action frameworks in marketing and digital sales contexts. Practical knowledge of Gen AI/LLM solutions (e.g., prompt engineering, retrieval-augmentedgeneration, evaluation methodologies, and model guardrails) and hands-on experience using Gemini and/or Azure AI for automation and customer experience use cases, Strong command of SQL and PL/SQL for advanced feature extraction with large-scale data on enterprise data platforms (e.g., Teradata, Oracle, Big Query) Familiarity with MLOps practices – such as version control, pipeline orchestration, model registry,CI/CD deployment patterns, monitoring, and lifecycle management – within Dataiku and incollaboration with Technology teams. Understanding of Responsible AI principles, including privacy, security, and bias mitigation for AI models and automated decisioning. Excellent understanding of telecommunications commercial practices and customer journeys, andthe ability to work cross-functionally with Product, Marketing, Sales, Digital, Technology teams.

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span><span><span><span><span><span><span><u><b>Job Description:</b></u></span></span></span></span></span></span></span><b>Details of the Division and Team</b><p><span>Deutsche Bank Research is responsible for economic and financial analysis within Deutsche Bank Group and covers asset allocation and all major industry sectors. We analyse relevant trends for the bank in financial markets, the economy and society, highlight risks and opportunities and act as consultant for the bank, its clients and stake-holders. </span></p><br><p><span>You will join the dbDIG team (Data Insights Group) that transforms alternative data, advanced analytics and artificial intelligence into client-facing investment research products and publications. In this role, you will shape how research questions become scalable data products, production-ready models, interactive dashboards, and practical artificial intelligence solutions used by analysts and clients. You will work at the intersection of research, data engineering, visualization, and artificial intelligence and help to demonstrate the bank’s applied analytics capability externally</span></p><br><p><b>What we will offer you</b></p><br><p>A healthy, engaged and well-supported workforce is better equipped to do their best work and, more importantly, enjoy their lives inside and outside the workplace. That’s why we are committed to providing an environment with your development and wellbeing at its center.</p><br><p><u>You can expect: </u></p><br><ul><li><p>Life Insurance&nbsp;</p><br></li><li><p>Accidental Death Insurance</p><br></li><li><p>&nbsp;Medical Insurance for you, your spouse and dependent children in country.</p><br></li><li><p>Flexible working arrangements</p><br></li><li><p>30 days of annual paid leave, plus public holiday &amp; Flexible Working Arrangement</p><br></li></ul><p><b>Your key responsibilities</b></p><br><ul><li><p><span>Drive the end-to-end alternative data agenda, partnering with analyst teams to turn research questions into scalable data products, from problem framing and data acquisition through signal development, statistical modeling, validation, and quality assurance.</span></p><br></li><li><p><span>Own data ingestion and validation standards for alternative datasets, using statistical, machine learning, and artificial intelligence-based checks to identify anomalies early and maintain high-quality inputs for modeling.</span></p><br></li><li><p><span>Collaborate with internal stakeholders across the full project lifecycle, while mentoring and helping manage junior team members working on data science projects.</span></p><br></li><li><p><span>Enhance data reporting by creating interactive dashboards, applications, geospatial maps, animations, and advanced visualizations.</span></p><br></li><li><p><span>Build practical artificial intelligence integrations, including application programming interfaces, model connection points, and secure access to internal data and research environments, to automate repetitive work and improve analyst productivity.</span></p><br></li></ul><p><b>Your skills and experience</b></p><br><ul><li><p><span>Experience building or managing alternative data, advanced analytics, or machine learning products in a research, financial services, or data-driven environment.</span></p><br></li><li><p><span>Strong capabilities in Python, PySpark, Tableau, data extraction, data quality testing, and working with large datasets in database or distributed computing environments.</span></p><br></li><li><p><span>Ability to translate complex research questions into clear analytical approaches, validated signals, and production-ready data products.</span></p><br></li><li><p><span>Experience creating dashboards, visualizations, or applications that make complex data easy for analysts and clients to understand and use.</span></p><br></li><li><p><span>Strong stakeholder management skills, with the ability to partner across research, technology, data engineering, and client-facing teams.</span></p><br></li><li><p><span>Proven ability to leverage AI tools to enhance productivity, optimize workflows to solve business problems, while applying critical judgment to ensure responsible and compliant use of data and AI outputs.</span></p><br></li></ul><p><b>How we’ll support you</b></p><br><ul><li><p>Flexible working to assist you balance your personal priorities</p><br></li><li><p>Coaching and support from experts in your team</p><br></li><li><p>A culture of continuous learning to aid progression</p><br></li><li><p>A range of flexible benefits that you can tailor to suit your needs</p><br></li><li><p>Training and development to help you excel in your career</p><br></li></ul><p><b>About us and our teams</b></p><br><p>Deutsche Bank is the leading German bank with strong European roots and a global network. Click here to see what we do.</p><br><p><b>Deutsche Bank &amp; Diversity</b></p><br><p>We strive for a <span><u>culture</u></span> in which we are empowered to excel together every day. This includes acting responsibly, thinking commercially, taking initiative and working collaboratively.</p><br><p>Together we share and celebrate the successes of our people. Together we are Deutsche Bank Group.</p><br><p>We welcome applications from all people and promote a positive, fair and inclusive work environment.</p><br> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span><span><span><span><span><span><span><u><b>Job Description:</b></u></span></span></span></span></span></span></span><b>Details of the Division and Team</b><p><span>Deutsche Bank Research is responsible for economic and financial analysis within Deutsche Bank Group and covers asset allocation and all major industry sectors. We analyse relevant trends for the bank in financial markets, the economy and society, highlight risks and opportunities and act as consultant for the bank, its clients and stake-holders. </span></p><br><p><span>You will join the dbDIG team (Data Insights Group) that transforms alternative data, advanced analytics and artificial intelligence into client-facing investment research products and publications. In this role, you will shape how research questions become scalable data products, production-ready models, interactive dashboards, and practical artificial intelligence solutions used by analysts and clients. You will work at the intersection of research, data engineering, visualization, and artificial intelligence and help to demonstrate the bank’s applied analytics capability externally</span></p><br><p><b>What we will offer you</b></p><br><p>A healthy, engaged and well-supported workforce is better equipped to do their best work and, more importantly, enjoy their lives inside and outside the workplace. That’s why we are committed to providing an environment with your development and wellbeing at its center.</p><br><p><u>You can expect: </u></p><br><ul><li><p>Life Insurance&nbsp;</p><br></li><li><p>Accidental Death Insurance</p><br></li><li><p>&nbsp;Medical Insurance for you, your spouse and dependent children in country.</p><br></li><li><p>Flexible working arrangements</p><br></li><li><p>30 days of annual paid leave, plus public holiday &amp; Flexible Working Arrangement</p><br></li></ul><p><b>Your key responsibilities</b></p><br><ul><li><p><span>Drive the end-to-end alternative data agenda, partnering with analyst teams to turn research questions into scalable data products, from problem framing and data acquisition through signal development, statistical modeling, validation, and quality assurance.</span></p><br></li><li><p><span>Own data ingestion and validation standards for alternative datasets, using statistical, machine learning, and artificial intelligence-based checks to identify anomalies early and maintain high-quality inputs for modeling.</span></p><br></li><li><p><span>Collaborate with internal stakeholders across the full project lifecycle, while mentoring and helping manage junior team members working on data science projects.</span></p><br></li><li><p><span>Enhance data reporting by creating interactive dashboards, applications, geospatial maps, animations, and advanced visualizations.</span></p><br></li><li><p><span>Build practical artificial intelligence integrations, including application programming interfaces, model connection points, and secure access to internal data and research environments, to automate repetitive work and improve analyst productivity.</span></p><br></li></ul><p><b>Your skills and experience</b></p><br><ul><li><p><span>Experience building or managing alternative data, advanced analytics, or machine learning products in a research, financial services, or data-driven environment.</span></p><br></li><li><p><span>Strong capabilities in Python, PySpark, Tableau, data extraction, data quality testing, and working with large datasets in database or distributed computing environments.</span></p><br></li><li><p><span>Ability to translate complex research questions into clear analytical approaches, validated signals, and production-ready data products.</span></p><br></li><li><p><span>Experience creating dashboards, visualizations, or applications that make complex data easy for analysts and clients to understand and use.</span></p><br></li><li><p><span>Strong stakeholder management skills, with the ability to partner across research, technology, data engineering, and client-facing teams.</span></p><br></li><li><p><span>Proven ability to leverage AI tools to enhance productivity, optimize workflows to solve business problems, while applying critical judgment to ensure responsible and compliant use of data and AI outputs.</span></p><br></li></ul><p><b>How we’ll support you</b></p><br><ul><li><p>Flexible working to assist you balance your personal priorities</p><br></li><li><p>Coaching and support from experts in your team</p><br></li><li><p>A culture of continuous learning to aid progression</p><br></li><li><p>A range of flexible benefits that you can tailor to suit your needs</p><br></li><li><p>Training and development to help you excel in your career</p><br></li></ul><p><b>About us and our teams</b></p><br><p>Deutsche Bank is the leading German bank with strong European roots and a global network. Click here to see what we do.</p><br><p><b>Deutsche Bank &amp; Diversity</b></p><br><p>We strive for a <span><u>culture</u></span> in which we are empowered to excel together every day. This includes acting responsibly, thinking commercially, taking initiative and working collaboratively.</p><br><p>Together we share and celebrate the successes of our people. Together we are Deutsche Bank Group.</p><br><p>We welcome applications from all people and promote a positive, fair and inclusive work environment.</p><br> </div>

About Commercial Bank Of Qatar<br><br>Commercial Bank, founded in 1975 and headquartered in Doha, plays a vital role in Qatar’s economic development by offering a range of personal, business, government, international and investment services.<br><br>We believe in empowering our employees, providing them with opportunities for growth and professional development.<br><br>By Joining us, you’ll be part of a workplace culture that fosters innovation, supports work-life balance, and encourages you to reach your full potential.<br><br>Join us in shaping the future of banking!<br><br>Job Summary<br><br>Responsible for developing advanced machine learning models for banking use cases including pricing optimization, customer propensity modelling, and recommendation systems. This senior role requires deep expertise in statistical modelling and machine learning combined with substantial banking and financial services domain knowledge . The position focuses on translating complex business problems in areas such as Risk, Finance, Retail Banking, and Wholesale Banking into actionable ML solutions. Will leverage their understanding of banking products, regulatory requirements, and financial metrics to build models that drive measurable business value. The role requires a balance of domain expertise and technical capability, with sufficient programming skills in Python and SQL to develop and deliver working prototypes that can be transitioned to production.<br><br>Key Accountabilities<br><br>ML Model Development Design and develop machine learning models for pricing optimization, including dynamic pricing, rate optimization, and fee structures. Build propensity models for customer behavior prediction including churn, cross-sell, upsell, and product adoption. Develop recommendation systems for personalized product offerings, next-best-action, and customer engagement. Banking Domain Application Apply deep banking domain knowledge to frame business problems as ML solutions with measurable outcomes. Partner with Risk, Finance, and business units to identify high-value modeling opportunities. Ensure models incorporate relevant regulatory requirements, risk considerations, and business constraints. Analysis & Insights Conduct exploratory data analysis to identify patterns, relationships, and modeling opportunities in banking data. Translate model outputs into actionable business recommendations and insights. Develop model performance metrics aligned with business KPIs and financial outcomes. Create data visualizations and reports for stakeholder communication. Prototyping & Delivery Develop working prototypes in Python demonstrating model functionality and business value. Create clear documentation of model methodology, assumptions, limitations, and use cases. Collaborate with ML Engineers and AI Engineers to transition prototypes to production systems. Stakeholder Collaboration Partner with business stakeholders to understand requirements and validate model outputs. Present model results, methodology, and recommendations to senior management. Contribute to model governance, validation, and documentation requirements. Ensure compliance with data policies, ethical standards, and regulatory requirements.<br><br>Key Competencies<br><br>Machine Learning & Statistics Expert knowledge of supervised and unsupervised learning techniques for classification, regression, and clustering. Deep experience with pricing models, propensity modeling, and recommendation systems. Strong foundation in statistical analysis, hypothesis testing, and experimental design. Familiarity with deep learning frameworks (Tensor Flow, PyTorch) for advanced use cases. Banking Domain Expertise Comprehensive understanding of banking products (Retail or Corporate business), services, and customer lifecycle. Knowledge of Risk functions including credit risk, market risk, and operational risk frameworks. Understanding of Finance functions including P&L drivers, cost allocation, and profitability analysis. Familiarity with regulatory requirements affecting model development (IFRS 9, Basel, etc.). Technical Skills Python for data analysis and model development (pandas, scikit-learn, XGBoost, etc.). SQL – Advanced user (Stored Procedures, Window functions, Temp Tables, Recursive Queries). Experience with data visualization and reporting tools. Familiarity with Git (Git Hub/Git Lab) for version control. Basic understanding of Spark for large-scale data processing. Awareness of MLOps practices and model deployment concepts (MLflow, TFX). Communication & Collaboration Ability to translate complex analytical concepts into business language for non-technical stakeholders. Strong presentation skills for executive-level communication. Experience working with cross-functional teams across business and technology. Agile methodologies (Kanban, Scrum) experience.<br><br>Qualifications & Experience<br><br>Master's degree or PhD in Finance, Economics, Statistics, Mathematics, or quantitative field strongly preferred.8+ years of experience in data science or quantitative analysis roles. Minimum 5 years of experience in banking or financial services industry is mandatory. Proven track record of delivering ML models in pricing, propensity, or recommendation domains. Background in Risk, Finance, or quantitative functions within banking preferred. Experience with model validation, governance, and regulatory requirements in financial services. Professional certifications in Risk (FRM, PRM) or Finance (CFA) are a plus.<br><br>Why Commercial Bank?<br><br> Best Digital Bank in the Middle East 2024 by World Finance and Best Mobile Banking App in the Middle East 2024 by Global Finance. An Innovation-Driven, Digital-First Environment where employees work with the latest tools and technologies to redefine banking Opportunities for Global Partnerships & International Exposure, connecting employees with global networks and perspectives. A focus on Employee Well-being & Work-Life Balance, ensuring a healthy and supportive environment for all team members Competitive Compensation & Benefits that ensure our employees are rewarded for their dedication and performance A strong Commitment to Diversity, Equity & Inclusion, fostering a culture that values every individual’s unique perspective. <br><br>At Commercial Bank, we don’t just offer careers, We shape futures by pioneering digital transformation in Qatar’s banking sector, blending digital-first approach to redefine banking through innovative solutions.<br><br>Disclaimer<br><br>We appreciate your interest in joining CBQ! Please note that only selected candidates will be contacted for further steps in the hiring process. This job posting is for informational purposes only, and CBQ reserves the right to modify, withdraw, or close it at any time without notice.

<p><strong>About Commercial Bank Of Qatar</strong></p><p>Commercial Bank, founded in 1975 and headquartered in Doha, plays a vital role in Qatar’s economic development by offering a range of personal, business, government, international and investment services.</p><p>We believe in empowering our employees, providing them with opportunities for growth and professional development.</p><p>By Joining us, you’ll be part of a workplace culture that fosters innovation, supports work-life balance, and encourages you to reach your full potential.</p><p>Join us in shaping the future of banking!</p><p><strong>Job Summary</strong></p><ul><li>Responsible for developing advanced machine learning models for banking use cases including pricing optimization, customer propensity modelling, and recommendation systems.</li><li>This senior role requires deep expertise in statistical modelling and machine learning combined with substantial banking and financial services domain knowledge .</li><li>The position focuses on translating complex business problems in areas such as Risk, Finance, Retail Banking, and Wholesale Banking into actionable ML solutions.</li><li>Will leverage their understanding of banking products, regulatory requirements, and financial metrics to build models that drive measurable business value.</li><li>The role requires a balance of domain expertise and technical capability, with sufficient programming skills in Python and SQL to develop and deliver working prototypes that can be transitioned to production.</li></ul><p><strong>Key Accountabilities</strong></p><ul><li>ML Model Development</li><li>Design and develop machine learning models for pricing optimization, including dynamic pricing, rate optimization, and fee structures.</li><li>Build propensity models for customer behavior prediction including churn, cross-sell, upsell, and product adoption.</li><li>Develop recommendation systems for personalized product offerings, next-best-action, and customer engagement.</li><li>Banking Domain Application</li><li>Apply deep banking domain knowledge to frame business problems as ML solutions with measurable outcomes.</li><li>Partner with Risk, Finance, and business units to identify high-value modeling opportunities.</li><li>Ensure models incorporate relevant regulatory requirements, risk considerations, and business constraints.</li><li>Analysis &amp; Insights</li><li>Conduct exploratory data analysis to identify patterns, relationships, and modeling opportunities in banking data.</li><li>Translate model outputs into actionable business recommendations and insights.</li><li>Develop model performance metrics aligned with business KPIs and financial outcomes.</li><li>Create data visualizations and reports for stakeholder communication.</li><li>Prototyping &amp; Delivery</li><li>Develop working prototypes in Python demonstrating model functionality and business value.</li><li>Create clear documentation of model methodology, assumptions, limitations, and use cases.</li><li>Collaborate with ML Engineers and AI Engineers to transition prototypes to production systems.</li><li>Stakeholder Collaboration</li><li>Partner with business stakeholders to understand requirements and validate model outputs.</li><li>Present model results, methodology, and recommendations to senior management.</li><li>Contribute to model governance, validation, and documentation requirements.</li><li>Ensure compliance with data policies, ethical standards, and regulatory requirements.</li></ul><p><strong>Key Competencies</strong></p><ul><li>Machine Learning &amp; Statistics</li><li>Expert knowledge of supervised and unsupervised learning techniques for classification, regression, and clustering.</li><li>Deep experience with pricing models, propensity modeling, and recommendation systems.</li><li>Strong foundation in statistical analysis, hypothesis testing, and experimental design.</li><li>Familiarity with deep learning frameworks (TensorFlow, PyTorch) for advanced use cases.</li><li>Banking Domain Expertise</li><li>Comprehensive understanding of banking products (Retail or Corporate business), services, and customer lifecycle.</li><li>Knowledge of Risk functions including credit risk, market risk, and operational risk frameworks.</li><li>Understanding of Finance functions including P&amp;L drivers, cost allocation, and profitability analysis.</li><li>Familiarity with regulatory requirements affecting model development (IFRS 9, Basel, etc.).</li><li>Technical Skills</li><li>Python for data analysis and model development (pandas, scikit-learn, XGBoost, etc.).</li><li>SQL – Advanced user (Stored Procedures, Window functions, Temp Tables, Recursive Queries).</li><li>Experience with data visualization and reporting tools.</li><li>Familiarity with Git (GitHub/GitLab) for version control.</li><li>Basic understanding of Spark for large-scale data processing.</li><li>Awareness of MLOps practices and model deployment concepts (MLflow, TFX).</li><li>Communication &amp; Collaboration</li><li>Ability to translate complex analytical concepts into business language for non-technical stakeholders.</li><li>Strong presentation skills for executive-level communication.</li><li>Experience working with cross-functional teams across business and technology.</li><li>Agile methodologies (Kanban, Scrum) experience.</li></ul><p><strong>Qualifications &amp; Experience</strong></p><ul><li>Master's degree in Finance, Economics, Statistics, Mathematics, or quantitative field strongly preferred.</li><li>8+ years of experience in data science or quantitative analysis roles.</li><li>Minimum 5 years of experience in banking or financial services industry is mandatory.</li><li>Proven track record of delivering ML models in pricing, propensity, or recommendation domains.</li><li>Background in Risk, Finance, or quantitative functions within banking preferred.</li><li>Experience with model validation, governance, and regulatory requirements in financial services.</li><li>Professional certifications in Risk (FRM, PRM) or Finance (CFA) are a plus.</li></ul><p><strong>Why Commercial Bank?</strong></p><ul><li>Best Digital Bank in the Middle East 2024 by World Finance and Best Mobile Banking App in the Middle East 2024 by Global Finance.</li><li>An Innovation-Driven, Digital-First Environment where employees work with the latest tools and technologies to redefine banking</li><li>Opportunities for Global Partnerships &amp; International Exposure, connecting employees with global networks and perspectives.</li><li>A focus on Employee Well-being &amp; Work-Life Balance, ensuring a healthy and supportive environment for all team members</li><li>Competitive Compensation &amp; Benefits that ensure our employees are rewarded for their dedication and performance</li><li>A strong Commitment to Diversity, Equity &amp; Inclusion, fostering a culture that values every individual’s unique perspective.</li></ul><p>At Commercial Bank, we don’t just offer careers, We shape futures by pioneering <strong>digital transformation</strong> in Qatar’s banking sector, blending <strong>digital-first</strong> approach to redefine banking through <strong>innovative</strong> solutions.</p><p><strong>Disclaimer</strong></p><p>We appreciate your interest in joining CBQ! Please note that only selected candidates will be contacted for further steps in the hiring process. This job posting is for informational purposes only, and CBQ reserves the right to modify, withdraw, or close it at any time without notice.</p>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <br> General Information <br> <br> Ref # <br> 235296 <br> <br> Location <br> Qatar-Doha <br> <br> Job family <br> Corporate &amp; Commercial <br> <br> <ul><li><span>Closing Date:</span> <span>2026-08-11</span></li></ul><br> <br> <br> <br> <br> <br> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <br> General Information <br> <br> Ref # <br> 235338 <br> <br> Location <br> Qatar-Doha <br> <br> Job family <br> Pilots &amp; Flight Operations <br> <br> <ul><li><span>Closing Date:</span> <span>2026-08-19</span></li></ul><br> <br> <br> <br> <br> <br> </div>