• Master fundamental theories and practical methodologies of consumer credit risk management.
• Apply statistical and machine learning techniques to analyze borrower default risks, and develop data-driven risk control models or strategies.
• Monitor key risk indicators (KRIs), identify potential risk issues, and optimize solutions.
• Collaborate closely with algorithm, product, and data warehouse teams to ensure effective implementation of risk strategies.

Qualifications

• Education: Bachelor’s degree or higher in Finance, Economics, Statistics, Mathematics, Computer Science, or related fields.
• Technical Skills: Proficiency in SQL, Python, and other statistical analysis tools. Solid programming capabilities.
• Learning Agility: Ability to quickly absorb new knowledge and adapt to fast-paced work environments.
• Analytical Skills: Strong logical thinking and data analysis capabilities; able to extr...