Equity Vol Quant Researcher (New York City Metropolitan Area)

About the job

A newly appointed Equity Volatility Portfolio Manager at a leading global multi-strategy hedge fund is building out a New York-based investment team.

The PM is seeking a highly technical Equity Volatility Quant Researcher to play a central role in developing the research, analytics and technology underpinning the strategy. This is an opportunity to join at an early stage, work directly with the PM and have meaningful influence over the development of the platform and investment process.

The role will span quantitative research, model development, data analysis and the implementation of production-quality tools. It would suit someone who combines strong knowledge of equity derivatives with the ability to turn research ideas into robust, usable systems.

Responsibilities

• Conduct quantitative research across equity volatility and derivatives markets.
• Develop systematic signals, relative-value frameworks and trade-selection methodologies.
• Build and enhance options pricing, volatility-surface, scenario-analysis and risk models.
• Analyse implied and realised volatility, skew, term structure, dispersion, correlation and volatility risk premia.
• Create research and portfolio analytics used in idea generation, position construction and risk management.
• Develop tools for backtesting, market monitoring, portfolio analysis and trade evaluation.
• Source, clean and structure large market and alternative datasets.
• Translate research prototypes into reliable, production-quality code.
• Improve the efficiency and scalability of the team’s research and trading infrastructure.
• Work closely with the Portfolio Manager on new strategies, portfolio construction and ongoing risk assessment.
• Investigate market behaviour and portfolio performance, communicating findings clearly and practically.

Candidate Profile

• Strong quantitative research or development experience within equity volatility, equity derivatives or a closely related systematic trading strategy.
• Deep understanding of options, volatility products and the behaviour of implied and realised volatility.
• Experience with areas such as volatility surfaces, skew, term structure, dispersion, correlation, variance risk premia or volatility relative value.
• Advanced Python programming skills and the ability to write clean, efficient and maintainable production code.
• Experience building research infrastructure, analytical tools, backtesting frameworks or trading applications.
• Strong knowledge of statistics, time-series analysis, numerical methods and derivatives pricing.
• Comfortable working with large, complex and imperfect financial datasets.
• Ability to take ownership of projects from initial research through implementation and production use.
• Commercial mindset and the ability to distinguish statistically interesting results from actionable investment opportunities.
• Clear communicator who can work effectively in a small, highly collaborative investment team.

Preferred Background

• Advanced degree in mathematics, statistics, physics, computer science, engineering, financial mathematics or another highly quantitative discipline.
• Experience at a hedge fund, proprietary trading firm, investment bank or specialist market maker.
• Familiarity with C++, Java or another high-performance programming language would be advantageous.
• Experience working with real-time market data, portfolio risk systems or electronic trading infrastructure would be beneficial.

For more information: View email address on apply.placed-app.com