Volatility Developer

Goldman Lloyds; New York (NY); On-site; USD 140,000 - 240,000; Full time

Job summary

Quantitative Volatility Developer position focusing on options and systematic research requires expert Python and software engineering skills. You will build high-performance backtesting and research frameworks, and develop infrastructure for systematic options and volatility strategies.

You’ll work with volatility analytics, signal generation, and risk analysis, collaborating with researchers and traders to move ideas from backtest to production while expanding involvement in strategy research

Qualifications

• Expert-level Python and strong software engineering fundamentals.
• Experience building backtesting engines or quantitative research platforms.
• Strong knowledge of equity derivatives, options and volatility.
• Experience with large-scale historical market datasets.
• Strong quantitative foundations in Mathematics, Statistics, Computer Science, Engineering, Physics.

Responsibilities

• Design and build high-performance Python backtesting and quantitative research frameworks.
• Develop infrastructure supporting systematic options and volatility strategies.
• Build tools for signal generation, strategy simulation, portfolio construction and risk analysis.
• Develop analytics around volatility surfaces, Greeks, hedging, P&L and derivatives risk.
• Work with large historical options and market datasets and improve the accuracy and performance of research environments.
• Partner directly with researchers and traders to take strategies from idea generation and backtesting through to production.
• Develop increasingly meaningful involvement in strategy research, testing new signals and evaluating systematic volatility opportunities.

Job description

Quantitative Volatility Developer – Options / Systematic Research

A leading hedge fund is seeking a Quantitative Volatility Developer to build and enhance the research infrastructure underpinning its systematic equity options and volatility strategies.This is a highly technical role working directly alongside volatility researchers and traders, combining sophisticated Python engineering, backtesting infrastructure and derivatives analytics.

Importantly, the role also offers a clear path to become increasingly involved in quantitative research, making it particularly attractive to strong quantitative developers looking to move closer to strategy development over time.

The Role

• Design and build high-performance Python backtesting and quantitative research frameworks.
• Develop infrastructure supporting systematic options and volatility strategies.
• Build tools for signal generation, strategy simulation, portfolio construction and risk analysis.
• Develop analytics around volatility surfaces, Greeks, hedging, P&L and derivatives risk.
• Work with large historical options and market datasets and improve the accuracy and performance of research environments.
• Partner directly with researchers and traders to take strategies from idea generation and backtesting through to production.
• Develop increasingly meaningful involvement in strategy research, testing new signals and evaluating systematic volatility opportunities.

Candidate Profile

• Up to 12 years of professional experience in quantitative development, research engineering or systematic trading technology.
• Expert-level Python and strong software engineering fundamentals.
• Proven experience building backtesting engines or quantitative research platforms.
• Strong knowledge of equity derivatives, options and volatility.
• Understanding of implied volatility, volatility surfaces, Greeks, options pricing and hedging.
• Experience working with large-scale historical market and options datasets.
• Strong quantitative foundations in Mathematics, Statistics, Computer Science, Engineering, Physics or a related discipline.
• Experience within a hedge fund, proprietary trading firm, investment bank or systematic investment environment.

For a strong quantitative developer looking to ultimately move closer to the research and strategy-generation side of systematic volatility trading, this offers a compelling progression path.

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