Quant Researcher

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Verition Fund Management seeks a Senior Quantitative Researcher with commodities futures experience to lead alpha research in a Dubai pod. This onsite role covers the end-to-end lifecycle from signal generation to deployment and monitoring, balancing creativity with discipline. You will generate signals using time series and approaches, own performance from research to trading, and collaborate with quant developers to deploy reliable models while contributing to portfolio construction and risk management. Qualifications: 4+ years in quantitative research, proven alpha in commodities futures, Python fluency, and knowledge of futures mechanics. To apply, share measurable alpha with results and links to code, and note experience in a lean pod with PMs and developers.

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.