About QNB
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. 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. 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. 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. QNB Group has an active community support program and sponsors various social, educational and sporting events.
Job Summary
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.
Main Responsibilities
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
Education And Experience Requirements
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.