VP, Quantitative Volatility Trading – Electronic Options

Goldman Sachs; Hong Kong; On-site; HKD 2,500,000 - 4,500,000; Full time

Job summary

Goldman Sachs seeks a Quantitative Volatility Researcher for its electronic market-making team in Hong Kong. You will focus on research, design, and calibration of automated pricing, quoting, and risk-management models in high-throughput options markets, collaborating with traders, researchers, and engineers.

The role demands deep expertise in options modeling, volatility dynamics, and large-scale data analysis, with strong Python and C++ programming skills.

Qualifications

• 5+ years of experience in quantitative research in options market-making or electronic trading.
• Strong foundation in options pricing theory and Greeks risk management.
• Proven ability to apply statistical methods to signal research or pricing problems.
• Experience analyzing large tick-by-tick and order-event datasets.
• Excellent collaboration and communication across traders, researchers, and engineers.
• Advanced degree preferred (Master’s or Ph.D.).

Responsibilities

• Research, calibrate, and enhance models for real-time pricing and volatility surfaces.
• Extract signals from market data and LOB dynamics.
• Design, backtest, and refine automated quoting and execution algorithms.
• Build simulation tools and backtests to evaluate strategy performance and risk.
• Work with traders and developers to productionize research prototypes.
• Evaluate expansion opportunities across products and geographies.
• Contribute to a disciplined, collaborative research culture.

Skills

Quantitative research

Options pricing

Volatility dynamics

Python

C++

Market data analysis

Communication

Advanced degree (MS/PhD)

Education

Master’s or Ph.D. in Mathematics/Statistics/Physics/CS

Bachelor’s with demonstrable experience

Tools

Python

C++

Job description

Goldman Sachs seeks a Quantitative Volatility Researcher for its electronic market-making team in Hong Kong. You will focus on research, design, and calibration of automated pricing, quoting, and risk-management models in high-throughput options markets, collaborating with traders, researchers, and engineers.

The role demands deep expertise in options modeling, volatility dynamics, and large-scale data analysis, with strong Python and C++ programming skills.