Risk Management - Wholesale Credit Risk Vice President

JPMorgan Chase JPMorgan Chase · Banking · Jersey City, NJ +1 · Commercial & Investment Bank

This role focuses on developing and implementing machine learning models for wholesale credit risk management at JPMorgan Chase. Responsibilities include leading model development, designing statistical and econometric models, developing stress capital models (CCAR, ICAAP, CECL), and utilizing AI/ML techniques for risk monitoring and predictive modeling on large datasets. The role requires strong programming skills in Python and knowledge of credit risk modeling, with experience in regulatory reviews being essential.

What you'd actually do

  1. Lead model development: analyze conceptual soundness of complex forecasting models, engines, and reserve methodologies; assess model behavior and suitability of forecasting models/engines for Wholesale Credit
  2. Design & Develop Models: Create, enhance, and maintain sophisticated statistical and econometric models for forecasting and risk management
  3. Develop Stress Capital modeling: To support exercises such as Comprehensive Capital Analysis and Review (CCAR), Internal Capital Adequacy Assessment Process (ICAAP), and CECL.
  4. Utilize and implement Machine Learning: AI/ML techniques for risk monitoring, predictive modeling, and analyzing large, complex, structured/unstructured datasets.
  5. Work with model implementation team, data team and production
  6. Evaluate model performance on a regular basis

Skills

Required

  • Solid theoretical and practical knowledge of statistical methods and models: generalized linear models, time-series analysis, clustering, decision trees, logistic regression.
  • Experience in handling large amount of panel data, and data cleaning/filtering.
  • Hands on programming in Python.
  • Basic knowledge on credit risk modeling both at single-obligor level and portfolio level.
  • Previous experience in writing documents for regulatory reviews.

Nice to have

  • Prior experience in wholesale credit is preferred.
  • Prior experience in PPNR modeling is strongly preferred.
  • R is good to have.

What the JD emphasized

  • experience in modeling of either balance forecasting (commitment, utilization, prepayment) and/or spread/GII/NII
  • writing documents for regulatory reviews

Other signals

  • Utilize and implement Machine Learning: AI/ML techniques for risk monitoring, predictive modeling, and analyzing large, complex, structured/unstructured datasets.
  • Lead model development: analyze conceptual soundness of complex forecasting models, engines, and reserve methodologies; assess model behavior and suitability of forecasting models/engines for Wholesale Credit
  • Design & Develop Models: Create, enhance, and maintain sophisticated statistical and econometric models for forecasting and risk management