Get To Know Our GX Bank TeamGX 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

Credit:

• To develop and implement risk modelling framework and portfolio analytics tools to manage Retail/ MSME credit exposures within the Bank.

• Develop Credit Risk scorecards and models 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.

• Support development of expected credit loss models to address IFRS9 requirements.

Fraud & Others:

• To design, develop and implement Fraud machine learning models using algorithms like logistic regression, decision trees, random forests, gradient boosting (XGBoost, LightGBM), and neural networks to detect and prevent fraudulent activities.

• Develop and maintain a comprehensive risk database and perform in-depth risk analysis.

• Support development and maintenance of analytics capability, e.g. AutoML, MLOps, data pipeline etc, for risk management purposes.

• Synchronise with group-wide frameworks, processes (including modelling), tools and reporting which support the desired outcomes for Risk Modelling & Data Science.

• Collaborate with the EcoSystem team to facilitate data sharing, exploratory data analysis (EDA) and advanced Risk modeling to maximize data synergy.

Requirements:

• 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 5 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.