Job Description

Lead the end-to-end development, implementation and enhancement of MFRS 9 ECL models across Retail and MSME portfolios. Develop 12-month and lifetime PD models, including term structures, point-in-time calibration and the incorporation of forward-looking macroeconomic information. Develop LGD models covering recovery patterns, cure behaviour, workout periods, collateral, costs and discounting. Develop EAD and credit conversion factor models for term loans and revolving credit facilities. Design and enhance ECL methodologies covering portfolio segmentation, default definitions, significant increase in credit risk, staging and multiple economic scenarios. Develop application, behavioural and collection scorecards using traditional statistical methods and, where appropriate, machine-learning techniques. Perform model calibration, back-testing, benchmarking, sensitivity analysis, stress testing and ongoing performance monitoring. Translate modelling methodologies into robust, modular and reproducible Python implementations. Build reliable analytical datasets and model pipelines using Python and SQL, working closely 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 the 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.

Job Requirements