Quantitative Research is an expert quantitative modeling group in J.P. Morgan, an unchallenged leader in financial engineering, derivatives modeling and risk management. With more than 500 analysts worldwide, Quantitative Research partners with traders, marketers and risk managers across all products and regions.
 
Quantitative skills are a core capability of J.P. Morgan, contributing critically to product innovation, effective risk management and appropriate financial and risk controls. The team's mission is to develop and maintain sophisticated mathematical models, cutting-edge methodologies and infrastructure to value and hedge financial transactions ranging from vanilla flow products to complex derivative deals, as well as improve the performance of algorithmic trading strategies and promote advanced electronic solutions to our clients worldwide. We also develop portfolio risk-measurement methodologies, quantify credit/market risk exposures and economic capital, work closely with trading desks to develop statistical arbitrage strategies and inventory management solutions.

Internship Insights

  • Developing mathematical models for pricing, hedging and risk measurement of derivatives securities
  • Developing mathematical models for algorithmic trading strategies as well as Delta-One trading strategies or inventory management
  • Supporting both OTC and electronic trading activities by explaining model behavior, identifying major sources of risk in portfolios, carrying out scenario analyses, developing and delivering quantitative tools, and supporting analytics
  • Assessing the appropriateness of quantitative models and their limitations, identifying and monitoring the associated model risk
  • Implementing risk measurement, valuation models or algorithmic trading modules in software and systems
  • Designing efficient numerical algorithms and implementing high performance computing solutions
  • Designing and developing software frameworks for analytics and their delivery to systems and applications

Requirements

  • Enrolled in a master’s or Ph.D. degree program in math, statistics, sciences, engineering, computer science, machine learning or other quantitative fields
  • Mastery of advanced mathematics with a deep knowledge of statistical modelling/data science or Stochastic Modeling (probability theory, stochastic calculus, partial differential equations, numerical analysis, optimization, statistics, econometrics, machine learning)
  • Exceptional software design and development skills using C++, Python, Java.
  • Knowledge of options pricing theory, trading algorithms or financial regulations a plus
  • Excellent analytical, quantitative and problem solving skills and demonstrated research skills
  • Strong communication skills (both verbal and written) and the ability to present findings to a non-technical audience
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