Job Scope

• Develop and validate credit risk models including ABC scorecard for lending products using statistical and machine learning techniques;
• Familiar with credit strategy for retail product including BNPL/Cash Loan product
• Familiar with and master various credit model algorithms, including but not limited to logistic regression, decision tree, random forest, GBDT, XGBoost, LightGBM, etc., and be able to reasonably choose and optimize according to specific business needs.
• Responsible for building and optimizing credit scoring models, including data collection, preprocessing, feature engineering, model selection, model training and evaluation, and the entire process.
• Can independently establish and improve credit models, and can adjust and optimize models for different business scenarios.
• Familiar with the relevant knowledge in the field of financial risk control, understand related laws and regulations, and can design feasible credit models based on actual business needs.

Requirements

• Strong background in statistics, mathematics, economics, or a related field.
• Proficiency in programming languages such as R, Python, or SQL.
• Experience with statistical modeling and predictive analytics.
• Good Understanding of credit risk modeling and scoring methodologies.
• Knowledge of data mining and machine learning techniques.
• Ability to analyze large datasets and extract meaningful insights.
• Familiarity with credit risk regulations and compliance standards.
• Effective communication and presentation skills to convey complex analysis results to stakeholders.

Please refer to job description.