Senior Data Science Expert

About Commercial Bank of Qatar

Founded in 1975 and headquartered in Doha, Commercial Bank plays a significant role in Qatar’s economic progress by providing a diverse range of personal, business, government, international, and investment banking services. The bank fosters a culture dedicated to employee growth, professional development, and innovation while supporting work-life balance to help every employee reach their potential.

Role Overview

The Senior Data Science Expert will design and implement sophisticated machine learning models tailored for banking challenges like pricing optimization, customer propensity analysis, and personalized recommendation systems. This senior position demands a blend of profound statistical and machine learning skills along with deep knowledge of banking and financial services. The incumbent will transform intricate business needs across Risk, Finance, Retail, and Wholesale Banking into pragmatic ML solutions leveraging an understanding of banking products, regulations, and financial metrics to produce measurable business impact. They must be proficient in Python and SQL to create and deliver prototypes ready for production deployment.

Key Responsibilities

• Develop machine learning models focused on dynamic pricing, rate optimization, and fee structuring.
• Create customer behavior propensity models including churn prediction, cross-sell, upsell, and product adoption forecasts.
• Build recommendation systems targeting personalized product offers and customer engagement enhancement.
• Apply deep banking domain expertise to translate business challenges into quantifiable ML model solutions.
• Collaborate with Risk, Finance, and other business units to discover valuable modeling opportunities incorporating regulatory and risk considerations.
• Perform exploratory data analysis to detect patterns and modeling possibilities within banking datasets.
• Interpret model results into practical business insights and recommendations.
• Define model performance metrics that align with business KPIs and financial goals, and prepare visualizations and reports for stakeholders.
• Develop functional Python prototypes demonstrating model effectiveness and business advantages with thorough documentation of methodologies, assumptions, and constraints.
• Work jointly with ML and AI engineers to deploy prototypes into production systems.
• Engage with stakeholders to gather requirements, validate outcomes, and present findings and recommendations to senior leadership.
• Ensure models adhere to data policies, ethical standards, model governance, validation, and regulatory requirements.

Expertise and Competencies

• Expertise in supervised and unsupervised machine learning techniques including classification, regression, and clustering.
• Strong experience with pricing, propensity, and recommendation modeling approaches.
• Solid foundation in statistical analysis, hypothesis testing, and experiment design.
• Familiarity with deep learning frameworks like TensorFlow or PyTorch for complex applications.
• Extensive knowledge of banking products, risk management (credit, market, operational), finance functions (P&L, cost allocation, profitability), and regulatory frameworks such as IFRS 9 and Basel.
• Proficiency in Python programming involving libraries such as pandas, scikit-learn, and XGBoost.
• Advanced SQL skills including stored procedures, window functions, temporary tables, and recursive queries.
• Experience with data visualization and reporting tools and version control using Git.
• Basic knowledge of Spark for large-scale data processing and understanding of MLOps and model deployment tools.
• Excellent communication skills to translate complex analytics into business language and effectively present to executive audiences.
• Experience in collaborating with cross-functional teams and working in Agile environments.

Qualifications and Experience

• Master’s degree in Finance, Economics, Statistics, Mathematics, or related quantitative discipline preferred.
• At least 8 years in data science or quantitative roles, with a minimum of 5 years in banking or financial services sector.
• Proven success delivering machine learning models focused on pricing, propensity, or recommendation tasks.
• Experience in Risk, Finance, or quantitative banking functions favored.
• Familiarity with model validation, governance, and financial regulatory compliance.
• Relevant professional certifications such as FRM, PRM, or CFA are advantageous.

Why Join Commercial Bank?

• Recognized as the Best Digital Bank and Best Mobile Banking App in the Middle East (2024).
• Innovative, digital-first working environment with access to cutting-edge technologies.
• Opportunities for international partnerships and diverse cultural exposure.
• Strong emphasis on employee well-being and maintaining work-life balance.
• Competitive salary and benefits that reward dedication and performance.
• Commitment to diversity, equity, and inclusion fostering a respectful workspace.

Additional Information

The bank is dedicated to shaping futures by leading digital transformation in Qatar’s banking sector through innovation. Please note that only shortlisted candidates will be contacted, and the job posting is subject to change or withdrawal without prior notice.