Senior ECL Modeller - MFRS9, Python & SQL

GXS; Petaling Jaya; On-site; MYR 180,000 - 300,000; Full time

Job summary

GX Bank Berhad, the Grab-led digital bank in Malaysia, seeks an experienced credit risk modeller to lead MFRS 9 ECL modelling for Retail and MSME portfolios. You will develop PD, LGD and EAD models using Python and SQL, build scorecards, and drive governance across model risk.

This role requires hands-on expertise and strong collaboration with data and business teams. The candidate should have 8+ years in credit risk/quant analytics, advanced degrees in quantitative fields, and a track record of

Qualifications

• At least 8 years in credit risk modelling, quantitative risk, data science, or advanced analytics in banking/finance.
• Hands-on MFRS 9/IFRS 9 ECL modelling with PD, LGD and EAD experience.
• Deep understanding of ECL concepts including 12-month and lifetime losses, staging, and forward-looking macro scenarios.
• Experience developing and monitoring credit risk scorecards for Retail, MSME, or similar portfolios.
• Strong Python for statistical modelling using pandas, NumPy, scikit-learn, statsmodels.
• Strong SQL skills with large, longitudinal credit datasets.
• Knowledge of modelling techniques: logistic regression, survival analysis, transition matrices, time-series, macroeconomic modelling, and recovery analysis.
• Experience managing the complete model lifecycle: data prep, methodology, implementation, monitoring, documentation, remediation.
• Sound understanding of model risk governance, validation standards, and regulatory expectations.
• Ability to communicate complex methodologies and modelling results to senior and non-technical stakeholders.

Responsibilities

• Lead end-to-end development, implementation and enhancement of MFRS 9 ECL models across Retail and MSME portfolios.
• Develop 12-month and lifetime PD models with term structures and macro information.
• Develop LGD models covering recovery, cure, workout periods, collateral, costs and discounting.
• Develop EAD and credit conversion factor models for term loans and revolving facilities.
• Design and enhance ECL methodologies including portfolio segmentation, staging, and multiple scenarios.
• Develop application, behavioural and collection scorecards using traditional statistics and ML where appropriate.
• Perform calibration, back-testing, benchmarking, sensitivity analysis, stress testing and monitoring.
• Translate modelling methodologies into robust Python implementations.
• Build reliable analytical datasets and model pipelines with Python and SQL, collaborating with Data Engineering/Tech teams.
• Produce model documentation and support internal validation, governance and audits.
• Partner with Credit Risk, Finance and Business teams to explain ECL movements and portfolio trends.
• Contribute to broader credit risk modelling, portfolio optimisation and capital-management frameworks.
• Provide technical guidance and mentorship to other modellers and analysts.

Skills

Python

SQL

Statistical modelling

Machine learning

Communication

Education

Bachelor’s or Master’s degree in Statistics, Mathematics, Econometrics, Data Science, Computer Science, Engineering, Finance or another quantitative discipline

Tools

Git

CI/CD

AWS

Job description

GX Bank Berhad, the Grab-led digital bank in Malaysia, seeks an experienced credit risk modeller to lead MFRS 9 ECL modelling for Retail and MSME portfolios. You will develop PD, LGD and EAD models using Python and SQL, build scorecards, and drive governance across model risk.

This role requires hands-on expertise and strong collaboration with data and business teams. The candidate should have 8+ years in credit risk/quant analytics, advanced degrees in quantitative fields, and a track record of