Quantitative Trading and Research – Equity Derivatives Exotics - Associate

J.P. Morgan’s Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world. 

The Quantitative Trading and Research (QTR) Equity Derivatives team is looking for a junior quant to focus on exotic products. The objective is to drive and implement analytics, optimization and modeling for Equity Exotic trading, with immediate focus on exotic risk management and lifecycle modeling.

Job Summary

As an Associate for the Quantitative Equity Derivatives Exotics team, you will make extensive use of quantitative techniques, including machine learning, to deliver end-to-end solutions for the business. This includes introducing a strategic framework to strengthen risk and P&L control and facilitate lifecycle management, developing derivative pricing and lifecycle models, as well as identifying and monitoring associated model risks.

Job responsibilities:

• Develop a scalable risk-management and lifecycle-modeling framework capable of handling the full range of products across all regions globally
• Model derivative products using C++ - Python hybrid programming to meet business requests.
• Drive payoff innovation using the product design framework and machine learning techniques.
• Streamline product review under the product design framework and provide clear model documentation to facilitate model approvals. 
• Evaluate quantitative methodologies including identifying and monitoring model risks associated with derivative valuation models.
• Support trading activities by explaining model behavior, identifying major sources of risk in portfolios and carrying out scenario analyses. 

Required qualifications, capabilities, and skills:

• 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 the application of Monte-Carlo simulation and finite-difference PDE in derivative pricing.
• Ability to communicate effectively with business stakeholders.
• Prior experience in a front-office quantitative research role.

Preferred qualifications, capabilities, and skills:

• Knowledge of risk management frameworks and regulatory requirements.