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Quantitative Trading & Research - Quantitative Researcher for Systematic Volatility Trading – Associate
mid · Data Science & Analytics
Are you interested in derivatives trading, quantitative modelling, market microstructure and data-driven investment strategies? Join Quantitative Trading & Research (QTR) group APAC Systematic Trading team to contribute to the development of systematic trading, hedging and pricing capabilities across listed and OTC derivatives markets.
As an Associate in the QTR Systematic Trading APAC team, you will work with trading, quantitative research, technology and data partners to research, backtest and implement systematic strategies. The role will involve empirical data analysis, model development, strategy research, production implementation support and ongoing performance monitoring. The candidate will contribute across the full research lifecycle, from idea generation and data analysis to model validation and live strategy review, with increasing ownership over time.
Job Responsibilities
- Work closely with trading desks to identify opportunities for systematic improvements in quoting, hedging, execution and risk management.
- Research, backtest and help implement quantitative strategies for derivatives trading and market making; develop data-driven models using market data, trade data, risk data and performance analytics.
- Design backtesting and simulation frameworks to evaluate strategy performance under realistic market conditions; analyze model performance using various metrics.
- Partner with technology teams to move research models into production workflows with monitoring, diagnostics and controls.
- Support live strategy monitoring, model calibration, performance review and production issue analysis.
- Communicate research and performance results clearly to trading and technology partners.
Required Qualifications, Capabilities, and Skills
- PhD or Master’s Degree in a quantitative discipline such as mathematics, statistics, computer science, engineering, physics, financial engineering or a related field.
- Strong quantitative and analytical skills, with ability to formulate trading questions as data and modelling problems.
- Relevant experience in quantitative research, systematic trading, derivatives, market microstructure, algorithmic execution or financial data analysis.
- Strong Python programming skills, including pandas, numpy and common scientific computing libraries.
- Ability to work with large, multi-source datasets and turn empirical analysis into robust conclusions.
- Good communication skills, with ability to explain research results, assumptions and limitations clearly.
- Practical mindset and interest in seeing models move from research into monitored production trading workflows.
Preferred Qualifications, Capabilities, and Skills
- Exposure to listed options, volatility products, market making, execution algos or systematic trading.
- Knowledge of KDB/q or experience querying large financial time-series datasets.
- Familiarity with event-driven systems, messaging or production trading platforms
- Experience with statistical modelling, optimization, machine learning or high-performance numerical computing.
- Experience with C++, Java or production software engineering is beneficial but not required.
- Understanding of equity derivatives trading data such as quotes, orders, fills, RFQs, inventory, risk, PnL and mark-outs.