Assistant Manager - Credit Risk Modeling

US - Assistant Manager - US Bank

•First Line of Defense, including Model Development, Model Monitoring, Recalibration, Model Tuning. •Develop Regulatory Capital Models compliant with Basel III/IV standards and IRB approaches. Estimate PD, LGD, EAD, and Prepayment for retail (Credit Cards, Residential Mortgage, HELOC, etc.) and wholesale (Commercial and Industrial, Commercial Real Estate, etc.) portfolios. •Develop and calibrate models for predicting Expected Credit Losses under US GAAP’s CECL and IFRS 9 standards. Integrate forward-looking perspectives, scenario weightings, lifetime loss parameters, and macroeconomic linkages. •Develop and maintain Underwriting and Origination Models including classification models for pre-approval, approve/decline, etc. and regression models for limit setting. •Design and implement models for Stress Testing and Scenario Analysis. Incorporate regulatory (CCAR, DFAST) and internal stress scenarios, projecting losses, default rates, and capital impacts under adverse conditions. •Develop and implement segmentation, pool assignment, and scorecard strategies as appropriate. Select and justify appropriate model methodology (traditional model vs ensemble machine learning model) based on portfolio characteristics and regulatory requirements. •Identify and source relevant financial, behavioral, and macroeconomic data, and perform data cleaning, feature engineering, and exploratory analysis to support robust modeling. •First Line of Defense, including Model Development, Model Monitoring, Recalibration, Model Tuning. •Develop Regulatory Capital Models compliant with Basel III/IV standards and IRB approaches. Estimate PD, LGD, EAD, and Prepayment for retail (Credit Cards, Residential Mortgage, HELOC, etc.) and wholesale (Commercial and Industrial, Commercial Real Estate, etc.) portfolios. •Develop and calibrate models for predicting Expected Credit Losses under US GAAP’s CECL and IFRS 9 standards. Integrate forward-looking perspectives, scenario weightings, lifetime loss parameters, and macroeconomic linkages. •Develop and maintain Underwriting and Origination Models including classification models for pre-approval, approve/decline, etc. and regression models for limit setting. •Design and implement models for Stress Testing and Scenario Analysis. Incorporate regulatory (CCAR, DFAST) and internal stress scenarios, projecting losses, default rates, and capital impacts under adverse conditions. •Develop and implement segmentation, pool assignment, and scorecard strategies as appropriate. Select and justify appropriate model methodology (traditional model vs ensemble machine learning model) based on portfolio characteristics and regulatory requirements. •Identify and source relevant financial, behavioral, and macroeconomic data, and perform data cleaning, feature engineering, and exploratory analysis to support robust modeling. •Advanced degree in Math, Statistics, Economics or any other Analytical disciplines. •Any Graduate + MBA in finance with relevant experience/exposure. •Additional certifications: Professional Certification such as FRM, CFA preferred.

Experience Level

Mid Level