Assistant Vice President, Data Science

About QNB Group

Founded in 1964 as Qatar's inaugural Qatari-owned commercial bank, QNB Group has evolved into the largest banking institution across the Middle East and Africa (MEA) region. Operating in over 31 countries through subsidiaries and affiliates on three continents, QNB Group offers an extensive variety of sophisticated financial products and services. The bank employs over 28,000 staff serving approximately 20 million customers via 1,000 branches and an ATM network of 4,300 machines. QNB is highly rated by major credit agencies including Standard & Poor’s (A), Moody’s (Aa3), and Fitch (A+), and has earned numerous accolades from leading international financial publications. Currently, QNB is recognized as the most valuable banking brand in the MEA area by Brand Finance Magazine. The Group also actively contributes to community welfare by supporting educational, social, and sports initiatives.

Role Overview

The Assistant Vice President in Data Science is pivotal in spearheading advanced analytics and AI-driven projects throughout the bank. Collaborating closely with business and operations leaders, the role focuses on delivering expert data science support, leveraging AI tools and analytical frameworks to produce strategic insights and actionable recommendations. Responsibilities span from hypothesis testing and machine learning deployments to implementing Large Language Models, predictive and prescriptive analytics, deep learning, and data visualization. The position supports senior management by crafting insightful reports and AI capabilities to aid decision-making and achieve impactful business results.

Main Responsibilities

• Deploy and track KPIs to assess the impact of Data & AI initiatives on business outcomes while integrating cost management principles to enhance efficiency.
• Implement Key Risk Indicators (KRIs) for effective management of risks associated with Data & AI solutions and coordinate capital and operational expenditure approvals with executive leadership.
• Contribute to executing the overall Data & Analytics strategy of QNB, ensuring the delivery of cost-effective and productivity-enhancing data and AI solutions aligned with organizational budgets and objectives.
• Work jointly with internal peers, divisional heads, and external partners to identify and apply data-driven AI solutions that create value for QNB and its clientele.
• Transform complex business challenges into comprehensive data science requirements to support strategic decisions.
• Offer strategic advice on AI adoption and data science applications within the bank while responding thoroughly to customer inquiries about banking products and AI-driven solutions.
• Adhere to service level agreements and develop robust interdepartmental collaborations to optimize turnaround times and achieve group goals.
• Produce accurate and timely data reports for auditors, compliance officers, finance, and risk units.
• Build advanced predictive models using machine learning techniques to generate significant insights and implement new statistical methods as required.
• Continuously evaluate AI model performance and maintain best practices in AI infrastructure, including cloud services, Spark, GPUs, and containerization.
• Maintain a deep understanding of business needs, system architectures, and user requirements to deliver optimized data and analytics solutions.
• Stay informed on the latest developments in machine learning, artificial intelligence, and data analytics via ongoing professional learning and participation in internal technical forums.
• Comply with all legal, regulatory, and internal policies related to data protection, fraud control, anti-money laundering, and counter-terrorism financing within the framework of operational risk management.
• Maintain confidentiality of customer and internal data, providing information on a need-to-know basis to senior management and regulatory bodies.
• Undertake other data science and AI-related duties as assigned by management to support organizational objectives.

Qualifications and Experience

• A university degree preferably in computer science, data science, software engineering, information systems, or a related quantitative discipline.
• A minimum of 10 years of relevant professional experience, particularly in data science roles.
• PhD holders in statistics, machine learning, computer science, natural sciences, or engineering fields are highly desirable.
• Specialized expertise in machine learning, AI, cognitive science, or data science confirmed by extensive hands-on experience developing AI solutions with machine learning, deep learning, and large language models.
• Practical knowledge and implementation experience with LLM-based solutions.
• Banking sector experience is advantageous.
• Strong skills in cloud technologies, Python programming, and full-stack engineering are essential.

Application Requirements

• Submission of a current resume or CV.
• Valid passport or Qatar ID copy.
• Academic certificate copy.