Quantitative Trading and Research, Equity Derivatives Exotics, Associate

JPMorgan Chase

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Quick summary

Work type
On-site
Location
New York, NY
Employment
Full-time
Posted
82 days ago
Freshness
Confirmed live today
Nearby
99+ roles within 25 mi

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Similar $170k
$122k $219k
below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $131,562–$209,406.

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About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 1226 open roles on FindRole.

Listed pay typically runs $156,750–$215,000 across 5 roles with salary data.

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At a glance

TL;DR · Quantitative Trading and Research, Equity Derivatives Exotics, Associate

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The Quantitative Trading and Research – Equity Derivatives Exotics - Associate joins the Quantitative Trading and Research Equity Derivatives team to focus on exotic products. This role involves driving and implementing analytics, optimization, and modeling for Equity Exotic trading, with an immediate focus on exotic risk management and lifecycle modeling. You will develop a scalable risk-management framework, model derivative products using C++ and Python hybrid programming, and drive payoff innovation using machine learning techniques. Responsibilities include evaluating quantitative methodologies, identifying model risks, and supporting trading activities through scenario analyses and explaining model behavior. The role requires expertise in derivatives pricing models, Monte-Carlo simulation, and finite-difference PDE. You will provide clear model documentation to facilitate approvals while managing the full range of products across all global regions.

Skills

C++ Python Machine Learning Monte-Carlo Simulation Finite-Difference PDE Statistical Analysis Numerical Packages Derivatives Pricing Risk Management Equity Derivatives

What you'll do

  • Develop a scalable risk-management and lifecycle-modeling framework for global products.
  • Model derivative products using a C++ and Python hybrid programming approach.
  • Drive payoff innovation using the product design framework and machine learning techniques.
  • Streamline product reviews and provide clear documentation to facilitate model approvals.
  • Identify and monitor model risks associated with derivative valuation models.
  • Explain model behavior and identify major risk sources in portfolios to support trading.
  • Carry out scenario analyses to support active trading activities.

What we're looking for

  • Master or PhD degree in a quantitative field from a top university.
  • 1-3 years of experience in derivatives quantitative research.
  • Strong programming skills in C++, Python, and numerical packages.
  • Experience with statistical analysis and machine learning.
  • Experience with derivatives pricing models and equity derivatives products.
  • Solid understanding of Monte-Carlo simulation and finite-difference PDE in derivative pricing.
  • Prior experience in a front-office quantitative research role.
  • Knowledge of risk management frameworks and regulatory requirements (preferred).

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