Quantitative Researcher

Job Description

Quantitative Researcher | Intraday Equities- Mid to senior level | NYC or Chicago

Join an established systematic investment firm to develop original alpha for its US equities stat arb business. You’ll take research from an initial hypothesis through to live trading, working closely with portfolio managers, engineers, and traders.

The mandate spans intraday and mid-frequency forecasting. You’ll use detailed quote and trade data to investigate how market microstructure, trading flows, and relationships across stocks can help predict returns.

The research

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• Develop and test signals across intraday and mid-frequency horizons, including opportunities linked to ETF and index flows.
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• Apply statistical and machine-learning methods to large equity datasets and test whether signals hold up out of sample.
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• Assess how transaction costs, market impact, capacity, and signal decay affect a signal’s value in a live portfolio.
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• Work with engineers and traders to deploy models and use live results to refine them. At the senior level, you’ll also help set research priorities and mentor junior researchers.
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Your background

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• Typically 2–7 years of quantitative research experience in equities statistical arbitrage, intraday forecasting, or a related systematic strategy.
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• Original research that has informed live trading, with the ability to explain what you contributed and what drove performance.
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• A quantitative degree and a strong grounding in statistics and empirical research. A PhD is a plus.
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• Strong programming skills, ideally in Python, and experience working with large market datasets. Exposure to SQL, Spark, Linux, or production trading systems is valuable.
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• The firm is willing to wait through non-competes. Message me for a confidential conversation about the team, research scope, and timing.
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