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CIB QR – Quantitative Research - Wholesale Credit Quantitative Research Quantitative Developer-Vice President

Req #: 170124958
Location: Jersey City, NJ, US
Job Category: Accounting/Finance/Audit/Risk
Job Description:
JP Morgan Chase
JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with operations worldwide. The firm is a leader in investment banking, financial services for consumers and small business, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world's most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Information about JPMorgan Chase & Co. is available at
The successful candidate will work to support stress-testing J.P. Morgan’s Wholesale Credit portfolios through development of forecasting tools to aid and validate model development. The unit is concerned with forecasting for regulatory exercises such as CCAR, ICAAP, Risk Appetite, and Loan Reserve forecasting. The candidate will help to design, implement, and validate forecast and valuation models and integration frameworks. In particular, the team is responsible for continuously delivering a prototyping platform for validating model performance and benchmarking production forecasts. The candidate will help to produce an extensible framework for integrating models and assumptions efficiently and robustly.

Core responsibilities:

  • Work with modeling teams to develop accurate prototype model implementations
  • Work with production implementation team to validate implementation of model revisions
  • Work with delivery team to continuously validate production implementation


  • B.S. (or higher) in computer science or related field and at least 4 years of software development  experience
  • Strong quantitative and numerical programming skills
  • Python numerical programming experience
  • Experience developing and measuring statistical models
  • Experience using centralized or distributed version control systems
  • Self-motivated to deliver quality product


  • Ph.D. or M.S. in the physical sciences, mathematics, statistics, or engineering with 4+ years of Python software development experience
  • Full software lifecycle participation
  • Experience in major Python numerical frameworks (numpy, pandas, scipy)
  • Experience developing distributed systems
  • Experience designing unit-tests and numerical benchmarks
  • Performance profiling experience
  • Significant experience developing classical statistical inference and machine-learning models
  • Experience conducting time-series analysis and developing forecasting models
  • Experience developing automated analytics and reporting tools or workflows
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