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Credit Modeling Manager
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- Econometric/statistical, machine learning, and other analytical modeling;
- Proficiency in analytical software and tools including Python, SAS, R, SQL and other applications, such as Microsoft Excel/VBA and Access;
- Retail and/or wholesale credit risk models, including underwriting scorecards, loss forecasting models, prepayment models, and/or complex discounted cash flow models;
- Statistical and machine learning techniques for analyzing financial data, including survival analysis, time series analysis, GLM, logistic regression, XGboost, LightGBM, Random Forest, Neural Networks, decision tree analysis, and cluster analyses;
- Statistical techniques for analyzing financial data, including sampling, optimization, logistic regression, linear regression, decision tree analysis, and cluster analyses;
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