Responsibility
- Perform in-depth data cleaning, feature engineering, and analysis of customer application data, behavioral data, and transaction data.
- Lead the fine-tuning, deployment, and practical application of Large Language Models (LLMs) in credit life cycle.
- Develop, validate, and monitor credit risk models and customer behavior prediction models.
- Prepare comprehensive model documentation, presentations, and business requirement specifications to ensure compliance with regulatory standards.
Requirements:
- Bachelor’s degree or higher in Computer Science, Information Systems, Statistics, Applied Mathematics, or a related quantitative field.
- 4+ years of experience in risk analytics or modelling (candidates with less experience may be considered for Deputy Credit Risk Manager), preferably in retail banking.
- Hands-on experience in fine-tuning, deploying, and optimizing LLMs, with knowledge of AI Agent design and development.
- Proficiency in Python and experience with deep learning frameworks.
- 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.