Data Scientist

Great Pyramid; Kapar; On-site; MYR 80,000 - 120,000; Full time

Job summary

A Malaysia-based motorcycle finance provider is seeking a Data Scientist to lead the development of credit scoring models and enhance risk analytics initiatives. This pivotal role involves evaluating customer applications, managing credit risk, and driving data-driven strategies. The ideal candidate should possess a Bachelor’s or Master’s degree in relevant fields and 3-6 years of experience in credit risk modeling. Skills in Python, R, SQL, and Power BI are essential, alongside strong analytical and communication skills. This role is an opportunity to make significant contributions in a data-driven environment.

Qualifications

• Experience in credit risk modeling, statistical analysis, or predictive modeling (3-6 years).
• Familiarity with regulatory frameworks related to credit risk (e.g., MFRS 9).
• Ability to work with large datasets, perform ETL, and build deployable models.

Responsibilities

• Develop, validate, and implement credit scoring models to assess customer loan applications.
• Monitor portfolio performance and delinquency trends.
• Work with SQL, Power BI, and statistical tools to analyze and visualize data.

Skills

Python

R

SQL

Power BI

Excel

Analytical thinking

Problem-solving

Communication skills

Education

Bachelors or Masters degree in Data Science, Statistics, Actuarial Science, Computer Science, Finance

Tools

Power BI

SQL

Python

R

Job description

Our Clientis a Malaysia-based motorcycle hire-purchase financing provider offering quick approvals, flexible 12- 60 month installment plans, and up to 90% financing coverage.

Company Overview

Our Clientis a Malaysia-based motorcycle hire-purchase financing provider offering quick approvals, flexible 12- 60 month installment plans, and up to 90% financing coverage.

Role Overview

They are seeking a Data Scientist to lead the development of advanced credit scoring models and broader risk analytics initiatives. This role is crucial in shaping how to evaluate customer applications, manage credit risk, and drive data-driven strategies across the company. You will work closely with the risk management team to design and implement models that comply with regulatory standards while enhancing operational efficiency.

Job Responsibilities

• Credit Scoring & Decisioning
  • Develop, validate, and implement credit scoring models to assess customer loan applications.
  • Automate approval decision processes in collaboration with IT and business teams.
• Risk Analytics & Portfolio Monitoring
  • Monitor portfolio performance, delinquency trends, and risk concentrations.
  • Perform data-driven analysis to support collections strategies, fraud detection, and customer behavior insights.
  • Provide inputs for MFRS 9 Expected Credit Loss (ECL) modeling and reporting.
• Data Management & Reporting
  • Work with SQL, Power BI, Excel, and statistical tools (Python, R) to process, analyze, and visualize data.
  • Deliver actionable dashboards and insights to management for informed decision-making.

Requirements

• Bachelors or Masters degree in Data Science, Statistics, Actuarial Science, Computer Science, Finance, or a related field.
• Strong proficiency in Python, R, SQL, Power BI, and Excel.
• 3-6 years of relevant experience in credit risk modeling, statistical analysis, or predictive modeling. Experience in financial services, fintech, banking, or other data-driven industries will be an advantage.
• Familiarity with regulatory frameworks related to credit risk (e.g., MFRS 9, or similar) is preferred, but candidates with strong quantitative and analytical skills from other industries will also be considered.
• Ability to work with large datasets, perform ETL, and build models that can be deployed for business operations.
• Excellent analytical thinking, problem-solving, and communication skills.