At J.P. Morgan, we are committed to fostering an environment where talented individuals can thrive and make a meaningful impact. As a Vice President in our Equity Volatility Research team in New York, you will play a pivotal role in developing quantitative tools for derivatives pricing analytics, hedging, back testing, and scenario analysis. Your work will help clients and internal teams identify portfolio risks and alpha opportunities. You will design optimal software frameworks for risk management and strategy models, contributing to innovative research in the derivatives space. If you are passionate about quantitative research and enjoy collaborating across teams, we encourage you to apply.

Job summary
As a member of the Equity Volatility Research team, you will develop quantitative tools for derivatives pricing analytics, hedging, back testing, and scenario analysis to help clients and internal counterparts identify portfolio risk and alpha opportunities. You will design optimal software frameworks for risk management and strategy models, and collaborate closely with internal teams to market the team's research.

Job responsibilities

Implement hedging strategies and back-testing for equity derivatives products, including exotics Develop tools for scenario analysis using historical and simulated market data for portfolios involving large data sets Use quantitative methods to identify model risk, market risk of derivative payoffs, and alpha opportunities Engage in new projects involving machine learning techniques and NLP to improve strategy performance Provide clear documentation and contribute to innovative research publications in equity volatility strategies, focusing on systematic approaches Collaborate closely with Sales, Structuring, and Trading teams Address client inquiries, produce customized analyses, and help market research findings

Required qualifications, capabilities, and skills

Bachelor’s, Master’s, or Ph.D. degree in a quantitative discipline High proficiency in coding with Python, C++, and R Basic understanding of derivatives and risk metric dynamics Knowledge of machine learning and big data is advantageous Previous experience in quantitative research or structuring at an investment bank, or relevant buy-side experience Excellent written and verbal communication skills, with strong analytical abilities Self-motivated, team-oriented, detail-focused, and capable of thriving in a fast-paced, dynamic environment

Preferred qualifications, capabilities, and skills

Prior experience in quantitative research, equity derivatives, or QIS structuring is a plus