Data Scientist

Kapar, Selangor
Tetap
Sepenuh masa

19 hari lepas

Company Overview: Our Client is 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 for 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 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.

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