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CIB QR - Quantitative Research - Credit Portfolio Group Associate/VP

Req #: 180021172
Location: New York, NY, US
Job Category: Accounting/Finance/Audit/Risk
Job Description:

JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $2.4 trillion and operations worldwide. The Firm is a leader in investment banking, financial services for consumers and small businesses, commercial banking, financial transaction processing, asset management and private equity. 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.


Credit Portfolio Group Quantitative Research (CPG QR) is responsible for research, development and support of models for quantification and management of counterparty and funding risks in the investment bank. The group is also responsible for margin modeling as well as credit risk capital calculation.
Core responsibilities:
  • Design and implement state of the art simulation models for counterparty and funding risk calculation
  • Produce best in class model documentation and technical presentation
  • Support dedicated trading desk and risk organization in pricing and management of counterparty and funding risks
  • Support credit risk capital team in calculation and verification of counterparty risk capitals
  • Work closely with LOB quantitative research teams to develop derivative pricing models
  • Liaise with technology for end-to-end deployment and testing of new models

  • Excellent analytical and problem solving abilities
  • Strong written and verbal communication skills
  • PhD in Math, Finance, Physics, Computer Science, Engineering or Master in quantitative finance program or similar
  • Understanding of probability theory, stochastic processes, numerical methods
  • Programming experience (C/C++ and Python, experience with software release cycle a plus)  
  • Machine learning and ability to work with data a plus
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