Job Description

Assistant Manager, Credit Risk Modeler (Data Scientist)

Role Overview

This role supports the Head of Credit Risk in developing, enhancing, and reviewing credit scoring models. The position plays a key role in building and maintaining predictive models to evaluate customer creditworthiness, repayment behavior, and portfolio performance.

Key Responsibilities

Develop, implement, and maintain quantitative models or scorecards to assess default likelihood, repayment behavior, affordability, recovery expectations, and portfolio volatility. Evaluate and monitor both internal and external credit scoring and financial forecasting models using traditional and advanced predictive technologies. Design and manage model parameters, user requirements, and system configurations for various customer segments. Conduct regular model performance monitoring, back-testing, and performance reporting. Collaborate with independent validators to ensure compliance with model governance frameworks and address validation findings promptly. Partner with key stakeholders to apply analytical insights in credit decisioning, business strategy formulation, risk appetite setting, and capital assessments. Identify emerging risk patterns, problem segments, and potential opportunities using data-driven analysis.

Requirements

Bachelor's degree in a quantitative field (Statistics, Mathematics, Applied Mathematics, Engineering, Data Science/Analytics, or related). Master's degree preferred. 5-7 years of relevant experience in risk analytics, model development, or credit risk management. Proficient in data manipulation and programming using

R

, Python

, or

SQL*.
Strong analytical, problem-solving, and quantitative modeling skills. Experience with consumer portfolio risk or financial modeling is an added advantage.

Benefits

RM450 monthly e-wallet allowance

RM250 broadband claim

per month

Comprehensive medical coverage

Career development and learning opportunities

Job Type: Full-time

Pay: RM7,500.00 - RM9,500.00 per month

Application Question(s):

Have you ever developed or implemented credit scoring or statistical models (e.g. PD, LGD, EAD, or behavioral scorecards)? Are you proficient in using R, Python, or SQL for data analysis and model building? * What is your expected salary?