Quant Trader - US Equities

We are seeking an experienced Quantitative Trader to develop, implement, and optimize systematic trading strategies across US equities. Working closely with quantitative researchers, developers, and other traders, you will identify trading opportunities, build quantitative models, and translate research insights into live trading strategies.

Key Responsibilities

• Research, develop, and deploy systematic trading strategies across US equities, including single stocks, ETFs, and equity indices.
• Identify and exploit short-term alpha opportunities using market data, statistical modelling, and quantitative analysis.
• Develop predictive signals and models for market making, statistical arbitrage, relative-value trading, and intraday strategies.
• Analyze market microstructure, order-book dynamics, execution quality, adverse selection, and transaction costs.
• Optimize pricing, quoting, position sizing, hedging, and execution logic to improve trading performance.
• Monitor live strategy performance, manage risk, and conduct PnL attribution to identify opportunities for improvement.
• Collaborate with quantitative researchers and software engineers to take strategies from research and backtesting through production deployment.
• Contribute to the development of trading infrastructure, research tools, and systematic risk-management frameworks.

Requirements

• 3 years of experience in quantitative trading, preferably in US equities, equity market making, statistical arbitrage, or high-frequency trading.
• Demonstrated track record of developing, implementing, or improving systematic trading strategies.
• Background in HFT, electronic market making, intraday alpha, closing auctions, or equity arbitrage.
• Direct ownership of trading strategies, risk limits, or PnL.
• Experience working in a proprietary trading firm, hedge fund, or systematic trading team.
• Proficiency in Python and/or C ; experience with high-performance trading systems is a plus.