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.

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