Quantitative Trading & Research - Systematic Trading - Associate

JPMorgan Chase & Co.; New York (NY); On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Comprehensive training and growth opportunities

Supportive work environment for professional development

Job summary

JPMorgan Chase & Co. in New York is looking for an Alpha Quant for the Equity Derivatives QTR team. This role involves end-to-end alpha research and strategy deployment, utilizing data analytics and machine learning to drive results in the financial markets.

Ideal candidates will possess a strong quantitative background, proficiency in programming, and excellent communication skills. The position offers comprehensive training and a supportive work environment focused on professional growth.

Qualifications

• Strong quantitative background and practical problem-solving skills.
• Direct working knowledge of signal research and alpha capture.
• Proficiency in programming languages like Python, KDB, C++, or Java.

Responsibilities

• Build end-to-end design and implementation for daily signal research.
• Contribute to production implementation of alpha signals.
• Develop robust backtesting and regime analysis frameworks.
• Partner with business on risk management for derivatives strategies.

Skills

Quantitative background

Signal research with market data

Programming (Python, KDB, C++ or Java)

Data analytics skills

Communication skills

Education

Strong graduate degree (MS or PhD) in a quantitative field

Tools

AI/ML tools

Job description

Are you ready to make an impact in Equity Derivatives trading? As a Quantitative Trading & Research (QTR) team member, you will drive innovation across the vol trading ecosystem by applying advanced data analytics, statistical modeling, and machine learning. Join our global team and leverage your skills to shape the future of financial markets.

We offer comprehensive training and growth opportunities to enhance your skills and advance your career. Our diverse team supports a wide range of business functions, providing a unique environment for professional development. We are committed to accommodating diverse needs and fostering an inclusive workplace.

Job Summary

As an Alpha Quant on the Equity Derivatives QTR team, you will focus on end-to-end alpha research and strategy deployment across equity options and volatility markets. You will help drive the alpha research agenda for Systematic Derivatives, using data analytics and software engineering to deliver research-to-production strategies. Your role will involve feature engineering from diverse data sources, building robust alpha calibration, attribution, and monitoring frameworks, partnering closely with trading, and implementing systematic strategies with strong attention to execution, hedging, and risk.

Job Responsibilities

• Work closely with trading to build end-to-end design and implementation of daily and intraday signal research and deployment infrastructure, with special focus on equity derivatives / Systematic derivatives.
• Contribute from idea generation to production implementation: perform research, design prototypes, implement alpha signals and systematic strategies; support daily usage, monitor performance, and iterate based on live feedback.
• Research and model equity options and volatility dynamics (e.g., surface arbitrage, term structure, skew, dispersion, event risk, RV) and translate insights into deployable systematic strategies.
• Develop and maintain robust backtesting, attribution, and regime analysis frameworks tailored to derivatives PnL drivers.
• Build models that integrate fundamental, quantitative, and microstructure features to support risk internalization and/or risk warehousing, using statistics, machine learning, or heuristics as appropriate.
• Partner with the business on alpha capture, risk recycling, hedging design, and position/risk management for derivatives strategies (including Greeks and scenarios).
• Collaborate broadly with QTR teams across regions to build reusable research libraries, tooling, and standardized workflows for experimentation, deployment, and monitoring.
• (Plus) Leverage AI/ML and modern AI tooling to accelerate research and improve developer productivity, with an understanding of AI productionization (model governance, evaluation, monitoring, and safe professional use of AI agents).

Required Qualifications, Capabilities, and Skills

• You have a strong quantitative background, as well as practical problem-solving skills.
• You have direct working knowledge of signal research with market data and other financial data, alpha capture, and risk warehousing, preferably in equity derivatives.
• You like working closely with trading desks, understanding their business, and have a strong mind‑set of ownership to have an impact on the way they operate.
• You demonstrate proficiency in code design and programming skills, with primary focus on Python, KDB, C++ or Java in a commercial environment.
• You have practical data analytics skills on real data sets gained through hands‑on experience, and can handle and analyze complex, large scale, high‑dimensionality data from various sources.
• You quickly grasp business concepts outside immediate area of expertise and adapt to rapidly changing business needs.
• You think strategically and creatively when faced with problems and opportunities. You always look for new ways of doing things.
• Your excellent communication skills, both verbal and written, can engage and influence partners and stakeholders.

Preferred Qualifications, Capabilities, and Skills

• Strong graduate degree (MS or PhD) in a quantitative field (Computer Science, Financial Engineering, Mathematics, Physics, Statistics, Economics, …).
• Strong expertise in statistics and machine learning in financial industry.
• Robust testing and verification practice.
• Direct experience with electronic trading, and knowledge of trading algorithms.
• 3 to 5 years’ experience in finance: market making, electronic trading, trading strategies (high to low frequency: market making, statistical arbitrage, option trading…), or derivatives pricing and risk management.
• Knowledge of equity derivatives and volatility products is a plus.
• Plus: experience leveraging AI for research and engineering workflows, and familiarity with productionizing AI (repeatable pipelines, evaluation/monitoring, model risk awareness) and using AI agents professionally.