Quant Trader - US Equities
Full-time
AAA Global
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.
Vacancy posted 9 hours ago
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