Quantitative Researcher (Systematic Option Strategies)

Location: New York, NY, United States; office-based role

Salary: USD 155,000–300,000 base salary per year, plus potential discretionary bonus

Company

Global financial markets organization serving institutional clients through trading, financing, investment products, and risk management.

What you will do

• Research, test, and implement systematic option market-making, signal-generation, and risk-management strategies.
• Develop forecasting models for volatility markets, including skew, smile, term structure, carry, cross-asset relationships, and market regimes.
• Design systematic vega and related-risk hedging strategies while accounting for P&L, transaction costs, liquidity, basis, and tail risks.
• Own the research lifecycle from idea generation, data processing, feature engineering, and backtesting through portfolio construction, validation, and performance attribution.
• Assess production performance, refine models as markets evolve, and build reusable analytical tools and shared research infrastructure.
• Partner with Traders, Researchers, Strats, and Engineers and communicate methods, assumptions, risks, and results to Trading and senior stakeholders.

Requirements

• MS or PhD in statistics, mathematics, physics, computer science, engineering, operations research, econometrics, quantitative finance, or a related quantitative discipline.
• Typically 4–8 years of applied quantitative research experience in systematic options or volatility trading, systematic macro, derivatives, cross-asset relative value, statistical arbitrage, or a closely related area.
• Demonstrated experience developing and validating predictive models, signals, strategies, or systematic hedging approaches.
• Strong understanding of options, volatility, and risk, including Greeks, volatility surfaces, carry and roll-down, P&L attribution, transaction costs, and tail behavior.
• Experience with options in FX, equities, rates, commodities, or another liquid macro asset class.
• Strong foundation in statistics, probability, time-series analysis, econometrics, machine learning, optimization, and experimental design.
• Strong programming skills and experience with large market datasets, research pipelines, and backtesting frameworks; Python, Java, or similar languages are beneficial.
• Track record of independent research ownership, sound judgment, rigorous analysis, clear communication, intellectual honesty, high standards, and effective collaboration in a fast-paced environment.

Nice to have

• Cross-asset experience.
• Proficiency in Python, Java, or similar programming languages.

Culture & Benefits

• Close collaboration with Traders in a markets and trading-facing environment.
• Work with public and proprietary firm data and research that can be deployed directly in live markets.
• Benefits and wellness offerings are generally available to active, non-temporary, full-time and part-time US employees working at least 20 hours per week.
• Potential eligibility for a discretionary bonus when employed at fiscal year-end.