Description

Responsibility:

• Responsible for in-depth data cleaning, feature engineering, and analysis of customer application data, behavioral data, and transaction data.
• Design, develop, and optimize machine learning-based credit scoring models and customer behavior prediction models.
• Develop data-driven credit risk strategies (e.g., underwriting, credit limit, and collections strategies) aligned with business objectives and risk appetite.
• Prepare comprehensive model documentation, validation reports, technical presentations, and business requirement specifications to ensure compliance with regulatory requirements.

Requirements:

• Bachelor's degree or higher in Statistics, Computer Science, Information Systems, Applied Mathematics, or a related quantitative field.
• Strong knowledge of Python and SAS, along with foundational and applied understanding of machine learning techniques including Random Forest and XGBoost.
• Prior experience with Large Language Models (LLM) or generative AI applications is a plus.
• Strong analytical skills, deep expertise in credit risk analysis, and the ability to exercise sound independent judgment.
• Excellent written and spoken English and Chinese; Fluency in Mandarin is advantageous.

If you are applying for in-scope position(s) under the Mandatory Reference Checking Scheme (i.e., A role carrying out regulated activities licensed by the IA, SFC & MPFA), you are required to undergo the Mandatory Reference Checking. Our responsible recruiter will inform you the details of the MRC process and the requirements in due course. For details, please click here .