Senior Quantitative Researcher — Equities Machine Learning & Statistical Arbitrage
Confirmed open June 19, 2026
- Location
- New York, NY
- Compensation
- Competitive base + bonus
- Firm Type
- Multi-strategy hedge fund
What You'll Be Doing
As a Senior Quantitative Researcher, you will play a pivotal role in the Equities Machine Learning and Statistical Arbitrage platform.
- Research and develop alpha signals for systematic equity strategies.
- Design and enhance statistical arbitrage and market-neutral investment models.
- Apply machine learning techniques to large-scale financial and alternative datasets.
- Conduct rigorous hypothesis testing, backtesting, and model validation.
- Develop predictive models for return forecasting, risk estimation, and portfolio optimization.
- Identify and evaluate new datasets and alternative data sources.
- Partner with portfolio managers to integrate research into live trading strategies.
- Improve research infrastructure and contribute to scalable research processes.
- Collaborate with engineering and technology teams to deploy production-ready models.
- Mentor junior researchers and contribute to the broader research agenda.
Who We're Looking For
- PhD in Statistics, Mathematics, Computer Science, Physics, Engineering, Machine Learning, Operations Research, Economics, or a related quantitative field.
- 5+ years of experience in quantitative research or a related field.
- Strong programming skills in Python, R, or similar languages.
- Expertise in machine learning techniques and statistical modeling.
- Proven track record of generating investment insights that lead to measurable portfolio performance.
Why This Role
This is an exceptional opportunity to join a leading multi-strategy hedge fund known for its innovative approach to quantitative investing. Collaborate with top-tier professionals and leverage cutting-edge technology to drive impactful investment strategies in a dynamic and supportive environment.
Interested in this role?
Apply in a couple of minutes — résumé and a few details.
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