Join a pioneering team at the forefront of systematic trading innovation. The Quantitative Trading & Research (QTR) group is responsible for systematic trading across FX, Rates, Commodities, Credit, Equity and a wide range of markets. Within QTR, AI Market Lab brings together quantitative research, modern artificial intelligence, market microstructure, and high-performance engineering to develop the next generation of electronic trading capabilities. Our work spans signal research, pricing, market making, execution, portfolio construction, risk management, and the production systems that support them.
Job Summary
As a Quantitative Trading & Research – Market Microstructure Researcher in the AI Market Lab, you will frame problems, build measurement and simulation machinery, run careful ablation studies, and develop models/strategies that hold up across venues, regimes, and operational constraints. The ideal candidate has worked close to live trading systems and can translate research insights into execution- and latency-aware designs.
This is a research-forward role. We are seeking a quantitative researcher with deep expertise in market microstructure and high- to medium-to-high-frequency trading to drive research on how electronic markets behave at fine time scales—and how that structure can be converted into robust, deployable systematic strategies.
Job Responsibilities
- Analyze high-frequency market data, including Level 2 and, where available, Level 3 or Level 4 order-book and order-event data, to identify predictive structure and trading opportunities.
- Develop alpha signals and trading features based on order flow, liquidity, queue dynamics, price formation, cross-venue behavior, and short-horizon market response.
- Design, backtest, and implement market-making and risk-taking strategies, including pricing, order placement, cancellation, queue-position management, fill-probability estimation, and inventory control.
- Develop realistic research and simulation methodologies incorporating latency, fees, rebates, market impact, adverse selection, and operational constraints.
- Optimize strategy performance across signal generation, portfolio or position sizing, execution, and intraday risk management.
- Work closely with traders, quantitative developers, technology partners, exchanges, and ECNs to move strategies into production and improve them using live performance and markout analysis