Global Banking & Markets, Quantitative Volatility Trading Researcher – Electronic Options Market Making, Vice President, Hong Kong
Goldman Sachs
Quantitative Volatility Trading, Goldman Sachs' electronic market-making team, is seeking a Quantitative Researcher to help grow its on-exchange options trading business in Hong Kong.
This role is suited to a researcher with a solid track record in derivatives modeling and automated trading who combines strong mathematical intuition with a practical, data-driven mindset. You will focus on the research, design, and calibration of automated pricing, quoting, and risk-management models in high-throughput electronic markets. Working closely with traders, quant researchers, and engineering partners, you will drive continuous strategy improvement across listed options markets while leveraging Goldman Sachs' global scale and liquidity franchise.
Responsibilities
- Research, calibrate, and enhance mathematical models for real-time options pricing and dynamic volatility surfaces
- Extract predictive signals and statistical patterns from tick-level market data and limit order book dynamics
- Design, backtest, and refine automated quoting and execution algorithms
- Build simulation tools, backtests, and diagnostics to evaluate strategy performance, inventory risk, and execution slippage
- Partner closely with traders to translate live market observations and microstructure phenomena into algorithmic improvements
- Work with quantitative developers and software engineers to transition research prototypes into high-performance production code
- Evaluate expansion opportunities across products, markets and geographies
- Contribute to a disciplined, collaborative research culture focused on rigorous experimentation and measurable trading impact
Skills and Experience
- 5+ years of experience in quantitative research within an options market-making, electronic trading, or systematic derivatives environment
- Strong foundation in options pricing theory, volatility dynamics, Greeks risk management, and order book microstructure
- Proven ability to apply rigorous statistical and mathematical methods to signal research, pricing, or execution problems
- Strong programming skills in Python for statistical analysis, data manipulation, and strategy backtesting
- Practical working proficiency in modern C++ for latency-sensitive execution and production modeling
- Experience conducting research on large-scale, high-dimensional tick-by-tick and order-event datasets
- Sound engineering and quantitative judgment balancing mathematical elegance with live implementation realities
- Strong communication skills and a collaborative approach to partnering across trading, research, and core engineering
- Advanced degree (Master’s or Ph.D. preferred, or Bachelor’s with demonstrable experience) in Mathematics, Statistics, Physics, Computer Science, or a related quantitative discipline
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