Quantitative Trading and Research Associate, Equity Derivatives Exotics

JPMorgan Chase

Confirmed live 2 days ago High trust

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Work type
On-site
Location
New York, NY
Posted
36 days ago
Freshness
Confirmed live 2 days ago
Nearby
99+ roles within 25 mi

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Similar $165k
$122k most similar roles pay here $208k

This listing doesn't post a salary. Most similar roles pay $129,962–$200,000.

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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 1117 open roles on FindRole.

Listed pay typically runs $186,160–$215,000 across 7 roles with salary data.

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

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The Quantitative Trading and Research – Equity Derivatives Exotics - Associate joins the QTR Equity Derivatives team to focus on exotic products. This role involves implementing analytics, optimization, and modeling for equity exotic trading with a specific focus on risk management and lifecycle modeling. The associate will develop scalable frameworks for global product ranges, build derivative pricing models using C++ and Python hybrid programming, and drive payoff innovation through machine learning techniques. Key responsibilities include streamlining product reviews, providing model documentation, evaluating quantitative methodologies, and performing scenario analyses to support trading activities. Candidates must possess a Master or PhD in a quantitative field and experience with Monte-Carlo simulation, finite-difference PDE, and statistical analysis. The role addresses the technical challenges of managing risk, monitoring model risks, and ensuring robust pricing for complex equity derivative products.

Skills

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

What you'll do

  • Develop a scalable risk-management and lifecycle-modeling framework for global equity products.
  • Model derivative products using C++ and Python hybrid programming to meet business requests.
  • Drive payoff innovation through the product design framework and machine learning techniques.
  • Streamline product reviews and provide clear documentation to facilitate model approvals.
  • Evaluate quantitative methodologies and monitor risks associated with derivative valuation models.
  • Support trading activities by explaining model behavior and performing scenario analyses.
  • Identify major sources of risk within portfolios to support front-office operations.

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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