Responsibility

• Responsible for defining data specifications and clarifying logical rules for various types of data (including risk data, financial data, and business data), as well as conducting in-depth data cleansing, feature engineering, and analytical tasks.
• Develop data-driven strategic solutions aligned with business objectives and risk appetite to support financial planning and business decision-making.
• Automate and optimize existing processes to enhance operational efficiency and accuracy.
• Prepare comprehensive model monitoring reports, validation reports, technical presentations, and business requirement specifications to ensure model performance and related strategies comply with regulatory and compliance 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 is desirable.
• Prior experience with Large Language Models (LLM) or generative AI applications is a plus.  
• Strong analytical skills, deep expertise in data analysis, and the ability to exercise sound independent judgment.  
• Excellent written and spoken English and Chinese; Fluency in Mandarin is advantageous.