Quant Trader - Stat Arb

We are seeking a dynamic Quantitative Trader to join our Statistical Arbitrage Desk, where you will play a critical role in developing and implementing systematic trading strategies across equities and futures markets globally. The ideal candidate will have a proven track record in signal research, combination, and portfolio optimization, with experience delivering strategies achieving a minimum 3+ Sharpe Ratio.

Responsibilities:

• Signal Research: Conduct comprehensive research to identify alpha-generating signals in equities and futures. Explore traditional and alternative data sources to uncover unique insights into market dynamics and trading opportunities.
• Signal Combination: Develop innovative methodologies to combine multiple signals into robust trading strategies. Utilize statistical methods, machine learning algorithms, and ensemble techniques to enhance signal quality and predictive power.
• Portfolio Optimization: Design and implement advanced portfolio optimization techniques to construct diversified portfolios that maximize risk-adjusted returns. Utilize mathematical optimization frameworks, risk models, and allocation methodologies to allocate capital efficiently across strategies and assets.
• Systematic Strategy Development: Collaborate with quantitative researchers, developers, and traders to translate research ideas into systematic trading strategies. Design and implement trading algorithms to execute strategies in an automated and scalable manner, leveraging firm’s low-latency infrastructure.
• Risk Management: Monitor and manage risk exposure across portfolios, employing robust risk management frameworks and position sizing techniques. Conduct stress testing, scenario analysis, and performance attribution to quantify and mitigate various sources of risk.

Qualifications:

• Advanced degree in a quantitative discipline such as Mathematics, Statistics, Economics, Physics, Computer Science, or Engineering. PhD preferred.
• Proven experience in quantitative trading, statistical arbitrage, or systematic trading, with a focus on equities and futures markets.
• Strong proficiency in programming languages such as Python, R, or C++ for data analysis, model development, and algorithmic trading.
• Extensive experience in signal research, signal combination, and portfolio optimization techniques.
• Exposure to alternative data sources and machine learning techniques for signal generation and trading strategy development.
• Deep understanding of financial markets, market microstructure, and trading dynamics.
• Excellent analytical skills with a rigorous and systematic approach to problem-solving.
• Ability to thrive in a collaborative, team-oriented environment and effectively communicate complex ideas.

NY Transparency Law:

Annual Base Salary Range for qualified candidates would be between $150,000 -225,000.