Lead Specialist, Risk Modelling & Data Science

GXBank; Selangor; On-site; MYR 120,000 - 180,000; Full time

Job summary

A leading digital bank in Malaysia seeks a data-driven professional experienced in risk modelling and analytics to enhance financial products. The role demands at least 8 years of expertise in credit modelling, data science, and strong skills in Python and SQL. Responsibilities include developing risk frameworks, scorecards, and maintaining risk databases in compliance with regulatory standards. Ideal candidates will possess a degree or Master’s in a related field, with CFA or similar certifications as a bonus.

Qualifications

• At least 8 years of experience in data science, risk management, business analytics, or data engineering.
• Highly motivated and analytical individual.
• CFA, FRM, BRM or Chartered Banker is a plus.

Responsibilities

• Develop and implement risk modelling framework and portfolio analytics tools.
• Create Credit Risk scorecards and models aligned with Basel requirements.
• Calibrate risk parameters for effective risk management.
• Perform annual reviews and stress testing of scorecards.
• Maintain a comprehensive risk database for ECL reporting.

Skills

Data analysis and interpretation

Credit modelling

Python programming

SQL proficiency

AWS Cloud technology

Education

Degree or Master’s in Data Science, Banking/Finance/Mathematics, Statistics or Engineering

Job description

GX Bank Berhad - the Grab-led Digital Bank - is the FIRST digital bank in Malaysia, approved by BNM to commence operations. We aim to leverage technology and innovation to serve the financial needs of the unserved and underserved individuals, and micro and small medium enterprises.

We are driven by our shared purpose and passion to bring positive transformation to the banking industry, starting with solutions that address the financial struggles of Malaysians and businesses.

Get to know the Role:

• To develop and implement risk modelling framework and portfolio analytics tools to manage Retail and MSME credit exposures within the Bank.
• Develop Credit Risk scorecards and models for Retail and MSME portfolios in accordance with Basel requirements using traditional and AI / ML modelling approaches.
• Calibrate risk parameters and optimise scorecard cut-offs to achieve sound risk management.
• Conduct scorecard annual review and portfolio stress testing.
• Develop and maintain a comprehensive risk database, preparation of ECL reporting and perform in-depth risk analysis.
• Hands‑on development of ECL model, i.e. PD, LGD and EAD models, in meeting MFRS9 requirements.
• Synchronise with group‑wide frameworks, processes (including modelling), tools and reporting which support the desired outcomes for risk modelling and capital optimisation.

The must haves:

• Passionate in Data which includes ETL, analyse, and interpret data patterns within a complex data environment.
• Well versed in credit modelling and/ or data science techniques (AI / ML models) which includes hands‑on model development and implementation.
• Highly proficient in coding (Python / SQL etc); experienced in AWS Cloud technology would be an added advantage.
• At least 8 years of experience in data science/ risk management/ business analytics/ data engineering.
• Self‑motivated, passionate and analytical.
• Degree or Master’s degree in Data Science, Banking/Finance/Mathematics, Statistics or Engineering.
• CFA / FRM / BRM / Chartered Banker would be an added advantage.