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CIB Risk – Quantitative Research Market Risk Model Development - Associate/VP

Req #: 180037056
Location: New York, NY, US
Job Category: Accounting/Finance/Audit/Risk
Potential Referral Amount: 3000 US Dollar (USD)
J.P. Morgan is a leader in financial services, offering innovative and intelligent solutions to clients in more than 100 countries with one of the most comprehensive global product platforms available. We have been helping our clients to do business and manage their wealth for more than 200 years and we keep their interests foremost in our minds at all times. This combination of product strength, intellectual capital and character sets us apart as an industry leader. J.P. Morgan is part of J.P. Morgan Chase & Co. (NYSE: JPM), a global financial services firm with assets of $2.0 trillion.
This is a model development position within the Market Risk Quantitative Research group with a focus on Market Risk Capital modeling, and other related Capital and Risk analytics (e.g. derivative Greeks, portfolio structure analysis, etc). The role affords the new team member opportunities to gain cross-asset experience in a wide range of business areas and its product and models, while contributing to the model development for business specific as well as bank-wide models.
Core Responsibilities:
  1. Developing VaR models for products in the credit, public finance and counterpart risk (CVA) areas.  The responsibilities for VaR model development will include VaR methodologies development, time series selection/data quality checks, implementation, VaR model performance analysis, testing and documentation, etc.
  2. Working with model review groups for the questions/issues during the model review
  3. BAU supporting for the VaR end users such as market risk management teams
  • Good communication and writing skills, ability to work in a group
  • Graduate degree in a technical field, such as Math, CS, Physics, or Engineering.
  • Expertise in C++ and/or Python.
  • Strong analytical and problem solving abilities.
  • Probability theory, financial math or stochastic calculus is a plus
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