Job responsibilitiesmaster 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 extract actionable insights from complex datasets. Communication & collaboration: excellent verbal and written communication skills; able to actively contribute to cross-functional teamwork. Language: fluency in the local language and professional working proficiency in english.