Quant Researcher
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About the Role
Verition Fund Management LLC ("Verition") is a multi-strategy, multi-manager hedge fund founded in 2008.
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Overview
Verition Fund Management LLC ("Verition") is a multi-strategy, multi-manager hedge fund founded in 2008.
Verition focuses on global investment strategies including Global Credit, Global Convertible, Volatility & Capital Structure Arbitrage, Event-Driven Investing, Equity Long/Short & Capital Markets Trading, and Global Quantitative Trading.
We are seeking a Senior Quantitative Researcher with strong experience in **commodities futures** to lead alpha research within a pod structure.
The role requires ownership of the **end-to-end research lifecycle**, from signal generation and backtesting through deployment and live monitoring.
Success in this environment requires a strong balance of research creativity, engineering discipline, and an understanding of the constraints of a production trading platform.
Responsibilities
- Research, develop, and deploy systematic trading strategies across global commodities futures markets.
- Generate alpha signals using time-series, cross-sectional, and regime-aware approaches.
- Own signal performance from research through live trading, including ongoing evaluation and refinement.
- Build and maintain Python-based research infrastructure aligned with the pod's production systems.
- Ensure research is reproducible, scalable, and designed with deployment constraints in mind.
- Work closely with quant developers to transition research into robust, production-ready models.
- Contribute to portfolio construction, capital allocation, and risk management frameworks within the pod.
- Incorporate liquidity, transaction costs, and capacity considerations specific to futures markets.
- Monitor live strategy performance, investigate deviations, and iterate on models as market conditions evolve.
- Partner with the PM to make data-driven decisions on capital allocation and strategy scaling.
Qualifications & Experience
- 4+ years of experience in quantitative research or systematic trading within a multi-manager or pod-based environment.
- Demonstrated success generating alpha in commodities futures.
- Strong proficiency in Python for research, backtesting, and analytics.
- Deep understanding of commodities futures mechanics, including rolls, term structure, seasonality, and contract specifications.
- Experience working within production constraints typical of multi-manager platforms (risk limits, turnover, capital usage).
- Experience deploying strategies into live trading systems.
- Familiarity with execution and transaction cost modeling for futures markets.
- Exposure to machine learning techniques applied to futures or time-series data.
- Strong communication skills and comfort operating in a lean, high-ownership pod structure.
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