Responsibility
- Perform in-depth data cleaning, feature engineering, and analysis of customer application data, behavioral data, and transaction data.
- Develop, validate, and monitor credit risk models and customer behavior prediction models.
- Design data-driven credit risk strategies (e.g., approval, credit limit and collections strategies) aligned with business objectives and risk appetite.
- Prepare comprehensive model documentation, presentations, and business requirement specifications to ensure compliance with regulatory standards.
Requirements:
- Bachelor’s degree or higher in Statistics, Computer Science, Information Systems, Applied Mathematics, or a related quantitative field.
- 5+ years of experience in risk analytics or modelling, preferably in retail banking.
- Proven experience in formulating and implementing credit risk strategies.
- Proficiency in Python and SAS, with hands-on experience in machine learning frameworks such as 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.
举报职位
