Senior Data Science Expert
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Key skills for this role
About the Role
Commercial Bank of Qatar is seeking a Senior Data Science Expert to develop advanced machine learning models for banking use cases including pricing optimization, customer propensity modeling, and recommendation systems.
Key Skills for This Role
Responsibilities
- 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
- 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
- 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
- Develop working prototypes in Python demonstrating model functionality and business value
- Create clear documentation of model methodology, assumptions, limitations, and use cases
Requirements
- 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
- Expert knowledge of supervised and unsupervised learning techniques
- Deep experience with pricing models, propensity modeling, and recommendation systems
- Strong foundation in statistical analysis, hypothesis testing, and experimental design
- Python for data analysis and model development
- SQL – Advanced user
- Comprehensive understanding of banking products, 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
Full Job Posting
Job Summary
- 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.
- 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.
Key Accountabilities
- 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.
- 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.
- 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.
- Develop working prototypes in Python demonstrating model functionality and business value.
- Create clear documentation of model methodology, assumptions, limitations, and use cases.
Key Competencies
- 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 (TensorFlow, PyTorch) for advanced use cases.
- 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.).
- 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 (GitHub/GitLab) for version control.
Qualifications & Experience
- 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.
Why Commercial Bank?
- 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.
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