A leading hedge fund is seeking a talented Quantitative Strategist with deep expertise in equity microstructure and algorithmic trading research to join the systematic equities team. You will focus on discovering and developing high-Sharpe intraday and short-horizon alpha signals using order book dynamics, market microstructure, and execution data. Your research will directly influence live trading strategies and execution algorithms with significant capital deployment.
Responsibilities
- Conduct in-depth microstructure research using tick-level and order book data to identify predictive signals related to liquidity dynamics, order flow imbalance, adverse selection, queue position, and short-term price formation.
- Research, design, and optimize intraday and short-horizon alpha signals for systematic equity strategies and execution algos.
- Develop and enhance algorithmic trading strategies, including passive posting logic, liquidity-seeking algorithms, optimal order sizing, volume surprise models, and dynamic hedging frameworks.
- Perform rigorous statistical analysis, backtesting, point-in-time validation, and transaction cost modeling to ensure signals and algos are robust and scalable.
- Collaborate closely with execution traders, portfolio managers, and developers to productionize research into live trading systems.
- Continuously monitor strategy performance and adapt models to evolving market microstructure conditions.
Requirements
- Advanced degree (MSc or PhD) in a quantitative field: Mathematics, Statistics, Physics, Computer Science, Financial Engineering, or related discipline.
- At least 3 years of experience in hands-on experience in equity microstructure research or algorithmic trading strategy development (sell-side electronic trading, prop trading, or hedge fund experience strongly preferred).
- Demonstrated ability to extract alpha signals from order book dynamics, tick data, and high-frequency market data.
- Strong programming skills in C++, C# or Java.
- Deep understanding of market microstructure concepts.
- Proven track record of improving execution algorithms or developing profitable short-horizon signals.
- Ability to work independently on research while collaborating effectively in a fast-paced, performance-driven environment.
