Verition Fund Management LLC
Equity Vol - Quant Researcher/Developer New New York, New York, United States
Verition Fund Management LLC, New York, New York, us, 10261
Verition Fund Management LLC ("Verition") is a multi-strategy, multi-manager hedge fund founded in 2008. Verition focuses on global investment strategies including Global Credit, Global Convertible, Volatility & Capital Structure Arbitrage, Event-Driven Investing, Equity Long/Short & Capital Markets Trading, and Global Quantitative Trading.
We are seeking a motivated and detail-oriented candidate with experience in single stock equity options and quantitative analysis to join one of our investment teams. The candidate will contribute to trading, risk management, alpha generation, and infrastructure development.
Key Responsibilities
Assist in developing and validating quantitative models for pricing, volatility modeling, and risk assessment of equity options.
Analyze large sets of market and historical data to identify trends, inefficiencies, and opportunities for model or strategy improvement.
Support ongoing research into equity options strategies, including volatility surfaces, skew analysis, and implied correlation modeling.
Help design and perform backtests for trading strategies and risk management tools using real and simulated data.
Develop and maintain analytical tools and dashboards in Python to help traders and researchers visualize performance metrics and model outputs.
Work closely with quantitative researchers, traders, and risk teams to translate research insights into practical applications for the trading desk.
Qualifications
Strong proficiency in Python, including experience with libraries such as pandas, NumPy, SciPy, and matplotlib.
Solid understanding of options theory, including the Black‐Scholes model, Greeks, implied volatility, and volatility surfaces.
Excellent quantitative and analytical skills with a strong ability to work with large datasets and complex models.
Strong verbal and written communication skills, with the ability to clearly explain quantitative findings to both technical and non-technical audiences.
Ability to produce accurate, high-quality work in a time-sensitive environment.
Familiarity with financial data providers
Experience with backtesting frameworks or quantitative research platforms.
Exposure to risk management concepts and portfolio analytics.
Knowledge of other programming languages such as SQL, R, or C++ is an advantage.
Salary Range $120,000 - $200,000 USD
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We are seeking a motivated and detail-oriented candidate with experience in single stock equity options and quantitative analysis to join one of our investment teams. The candidate will contribute to trading, risk management, alpha generation, and infrastructure development.
Key Responsibilities
Assist in developing and validating quantitative models for pricing, volatility modeling, and risk assessment of equity options.
Analyze large sets of market and historical data to identify trends, inefficiencies, and opportunities for model or strategy improvement.
Support ongoing research into equity options strategies, including volatility surfaces, skew analysis, and implied correlation modeling.
Help design and perform backtests for trading strategies and risk management tools using real and simulated data.
Develop and maintain analytical tools and dashboards in Python to help traders and researchers visualize performance metrics and model outputs.
Work closely with quantitative researchers, traders, and risk teams to translate research insights into practical applications for the trading desk.
Qualifications
Strong proficiency in Python, including experience with libraries such as pandas, NumPy, SciPy, and matplotlib.
Solid understanding of options theory, including the Black‐Scholes model, Greeks, implied volatility, and volatility surfaces.
Excellent quantitative and analytical skills with a strong ability to work with large datasets and complex models.
Strong verbal and written communication skills, with the ability to clearly explain quantitative findings to both technical and non-technical audiences.
Ability to produce accurate, high-quality work in a time-sensitive environment.
Familiarity with financial data providers
Experience with backtesting frameworks or quantitative research platforms.
Exposure to risk management concepts and portfolio analytics.
Knowledge of other programming languages such as SQL, R, or C++ is an advantage.
Salary Range $120,000 - $200,000 USD
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