CIB - QR - Quantitative Research - Market Risk - VP

The Programme

This position is within the Market Risk Quantitative Research Group (MRQR). MRQR is a global team which is responsible for building the models and infrastructure used for the risk management of market risk such as of VAR and stress. The MR QR team in Mumbai will therefore plays a critical role and supports the activities of Market risk QR group globally.

This is a quantitative Analytics position within the Market Risk Core Infrastructure, Model Performance & Time Series team of MR QR group with a focus on infrastructure and model performance, 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.

What You Will Do

  • Work on the implementation of the next generation of Market Risk analytics platform.
  • Integration of pricing models.
  • Work on the delivery for Market Risk analytics.
  • Model performance analysis.
  • Improvement of performance and scalability of analytics algorithms.
  • Automation of the models monitoring: Automated detection & identification of model issues.

Overall, the candidate will need to work closely with teams in Asia-Pacific and/or London and/or New York and will need to be proactive to improve the Market Risk analytics and strategic platform, access and learn J. P. Morgan’s highly sophisticated solutions.

Required Skills and Abilities

  • Graduate degree in a technical field, such as Math, CS, Physics, or Engineering.
  • Good interpersonal and communication skills, ability to work in a group.
  • Expertise in C++ and/or Python, including experience with numpy, scipy and/or pandas.
  • Expertise in data structures, standard algorithms and OO design.
  • Strong software design skills and implementation skills.
  • Strong analytical and problem solving abilities.
  • Pricing models theory or stochastic calculus is a plus.
  • Development using multi-threading, GPU, MPI, grid, or other HPC technologies is a plus.