Commodities Quant Analyst
Verition Group LLC
Salary not disclosed
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Description
Firm Overview
Verition Fund Management LLC (“Verition”) is a multi-strategy, multi-manager hedge fund founded in 2008. Verition focuses on global investment strategies including Fixed Income & Macro, Event & Multi-Asset RV, Equity L/S & Capital Markets, and Quantitative Trading.
Role Overview
Verition is seeking a Quantitative Analyst to join a commodities-focused investment pod in Houston. This is a highly research-oriented role working directly alongside an experienced Portfolio Manager to develop differentiated investment signals using alternative data and quantitative research techniques. The successful candidate will combine a strong foundation in statistics, financial modeling, and Python with a genuine curiosity for uncovering new sources of alpha.
Rather than focusing on software engineering, this individual will spend their time researching markets, identifying unique datasets, testing hypotheses, and developing predictive signals that can be incorporated directly into the investment process.
A significant portion of the role will involve sourcing, analyzing, and modeling alternative datasets related to global commodity markets. This includes working with data such as crude oil vessel tracking (AIS), shipping and freight activity, pipeline flows, refinery operations, storage and inventory data, weather, satellite imagery, and other non-traditional datasets. The objective is to transform raw information into robust, statistically validated signals that provide a measurable investment edge.
Responsibilities
- Develop financial time series models and predictive forecasting techniques across energy and commodity markets.
- Research, evaluate, and incorporate alternative datasets into the investment process.
- Design, test, and validate alpha signals through rigorous statistical analysis and backtesting.
- Build research pipelines to clean, organize, and analyze large structured and unstructured datasets.
- Leverage AI and machine learning techniques to improve feature engineering, accelerate research, and identify differentiated investment opportunities.
- Collaborate with the Portfolio Manager to rapidly prototype new ideas and continuously refine investment models as market dynamics evolve.
Qualifications
- Strong proficiency in Python and the broader scientific computing ecosystem, including Pandas, NumPy, SciPy, and scikit-learn.
- Experience with financial time series analysis, statistical modeling, feature engineering, and hypothesis testing.
- Knowledge of backtesting frameworks, predictive modeling, and signal evaluation techniques.
- Experience applying machine learning techniques and modern AI tools, including large language models, to quantitative research workflows.
- Proficiency with SQL, cloud-based data platforms, and working with large-scale structured and unstructured datasets.
- Interest in commodities, global markets, and alternative data research.
- Excellent written and verbal communication skills.
- High level of intellectual curiosity, strong work ethic, and a keen attention to detail.
- Ability to work effectively in a team-oriented, fast-paced, and dynamic environment
Benefits
- stock options
About this role
Verition's commodities pod in Houston is looking for a quant analyst to build investment signals from alternative data sources—think vessel tracking, satellite imagery, refinery operations, and weather patterns. You'd work closely with a Portfolio Manager on a research-heavy workflow: sourcing datasets, testing hypotheses, validating signals through backtesting, and feeding predictive models directly into the investment process. This is fundamentally about discovering alpha through rigorous statistical analysis rather than building production systems.
You'll need solid Python skills (Pandas, NumPy, scikit-learn), experience with financial time series and statistical modeling, and comfort working with SQL and cloud data platforms. The role expects you to apply machine learning and modern AI tools to accelerate research, but the emphasis is on the research itself—hypothesis testing, feature engineering, and signal design. A genuine interest in commodities and alternative data, combined with intellectual curiosity and attention to detail, matters as much as technical credentials.
This suits someone who enjoys detective work in markets, wants to learn commodities deeply, and prefers rapid prototyping and collaboration over long software engineering cycles. The in-office requirement in Houston reflects the tight working relationship with the Portfolio Manager and the pod's research-focused culture.
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Pay for this role
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