Lead Data Scientist

We are looking for an experienced credit risk modeller to lead the development of Expected Credit Loss (ECL) models for our Retail and MSME portfolios.

Key Responsibilities:

• Lead the end-to-end development and enhancement of IFRS 9 ECL models across Retail and MSME portfolios.
• Develop 12-month and lifetime Probability of Default (PD) models, including term structures, point-in-time calibration, and incorporation of forward-looking macroeconomic information.
• Develop Loss Given Default (LGD) models covering recovery patterns, cure behaviour, workout periods, collateral, costs, and discounting.
• Develop Exposure at Default (EAD) and credit conversion factor models for term loans and revolving credit facilities.
• Design and enhance ECL methodologies covering portfolio segmentation, default definitions, increase in credit risk, staging, and multiple economic scenarios.
• Develop application, behavioural, and collection scorecards using traditional statistical methods and machine-learning techniques.
• Perform model calibration, back-testing, benchmarking, sensitivity analysis, stress testing, and ongoing performance monitoring.
• Translate modelling methodologies into modular and reproducible Python implementations.
• Build reliable analytical datasets and model pipelines using Python and SQL, working with Data Engineering and Technology teams.
• Produce comprehensive model documentation and support independent validation, audit, governance committees, and regulatory reviews.
• Partner with Credit Risk, Finance, and Business teams to explain ECL movements, portfolio trends, and financial impact of model changes.
• Contribute to the Bank's broader credit risk modelling, portfolio optimisation, and capital-management frameworks.
• Provide technical guidance and mentorship to other modellers and analysts.

QUALIFICATIONS:

• At least eight years of relevant experience in credit risk modelling, quantitative risk, data science, or advanced credit analytics within banking, financial services, or consulting.
• Hands-on experience developing IFRS 9 ECL models, with demonstrated expertise in PD and practical experience across LGD and EAD modelling.
• Experience with ECL concepts, including 12-month and lifetime expected losses, staging, significant increase in credit risk, and forward-looking macroeconomic scenarios.
• Experience developing and monitoring credit risk scorecards for Retail, MSME, or similar lending portfolios.
• Advanced proficiency in Python for statistical modelling and data analysis, using libraries such as pandas, NumPy, scikit-learn, and statsmodels.
• Strong SQL experience working with large, complex, and longitudinal credit datasets.
• Knowledge of relevant modelling techniques, including logistic regression, survival analysis, transition matrices, time-series or macroeconomic modelling, and recovery analysis.
• Experience managing the complete model lifecycle, including data preparation, methodology development, implementation, monitoring, documentation, and remediation.
• Sound understanding of model risk governance, validation standards, and regulatory expectations.
• Ability to communicate complex methodologies and modelling results clearly to senior, technical, and non-technical stakeholders.
• Bachelor's or Master's degree in Statistics, Mathematics, Econometrics, Data Science, Computer Science, Engineering, Finance, or another quantitative discipline.

Good to Have:

• Experience with Basel credit risk models, IRB models, stress testing, or capital modelling.
• Experience deploying models into production and working with Git, automated testing, CI/CD, or model-monitoring frameworks.
• Familiarity with AWS services and cloud-based data or modelling platforms.
• Experience in digital banking, fintech, or portfolios with limited historical data.
• Professional qualifications such as FRM, CFA, Chartered Banker, or an equivalent risk qualification.

ADDITIONAL INFORMATION: Life at Grab We care about your well-being at Grab, here are some of the global benefits we offer:

• We have your back with Term Life Insurance and comprehensive Medical Insurance.
• With GrabFlex, create a benefits package that suits your needs and aspirations.
• Celebrate moments that matter in life with loved ones through Parental and Birthday leave, and give back to your communities through Love-all-Serve-all (LASA) volunteering leave.
• We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges.