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Commodities Quant Research Jobs (NOW HIRING)

Verition Group LLC

Commodities Quant Analyst

Houston, TX · On-site

Role Overview Verition is seeking a Quantitative Analyst to join a commodities-focused investment ... This is a highly research-oriented role working directly alongside an experienced Portfolio Manager ...

Verition Group LLC

Commodities Quant Analyst

Houston, TX · On-site

Role Overview Verition is seeking a Quantitative Analyst to join a commodities-focused investment ... This is a highly research-oriented role working directly alongside an experienced Portfolio Manager ...

AQR Capital Management

$225K - $245K/yr

S. in a quantitative field (e.g. Finance, Economics, Computer Science, Math, Engineering etc.) * 2-3 years' work experience at a quantitative finance firm, with exposure to commodities, futures ...

PIMCO

Quantitative Research Analyst

Newport Beach, CA · On-site

... Desk Quant to join our front-office Commodities Analytics team in Newport Beach. The role will ... Research, back-test and maintain systematic, option and quantitative investment strategies * Apply ...

PIMCO

Quantitative Research Analyst

Newport Beach, CA · On-site

... Desk Quant to join our front-office Commodities Analytics team in Newport Beach. The role will ... Research, back-test and maintain systematic, option and quantitative investment strategies * Apply ...

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$52.5K

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How much do commodities quant research jobs pay per year?

As of Sep 11, 2026, the average yearly pay for commodities quant research in the United States is $119,165.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,500.00 and $152,500.00 per year, depending on experience, location, and employer.

What is commodities quant research?

Commodities Quant Research involves using quantitative methods, such as statistical analysis, mathematical modeling, and computer algorithms, to analyze and forecast commodity markets. Professionals in this field develop trading strategies, manage risk, and optimize portfolios by leveraging large datasets and advanced analytics. Their work supports trading desks and investment teams in making informed decisions about commodities like oil, gas, metals, and agricultural products.

What are the key skills and qualifications needed to thrive as a commodities quant researcher?

To thrive as a Commodities Quant Researcher, you need a strong background in quantitative analysis, statistics, and financial modeling, typically supported by an advanced degree in mathematics, finance, physics, or engineering. Expertise in programming languages like Python, R, or MATLAB, and familiarity with data analysis platforms and risk management systems are essential. Strong problem-solving abilities, attention to detail, and effective communication skills help you convey complex findings to both technical and non-technical stakeholders. These skills are crucial for developing robust trading strategies, accurately analyzing market trends, and driving data-driven decision-making in the fast-paced commodities market.

What are the typical challenges faced by professionals in commodities quant research, and how can they effectively address them?

Professionals in Commodities Quant Research often encounter challenges such as modeling market volatility, incorporating unpredictable geopolitical events, and managing large, complex datasets. Staying updated with the latest quantitative methods and technological advancements is essential to remain effective in this fast-paced environment. Collaborating closely with traders, risk managers, and data engineers helps in refining models and ensuring their practical applicability. Regularly backtesting strategies and adapting to new data sources can help address these challenges and drive better decision-making.

What are popular job titles related to Commodities Quant Research jobs?

For Commodities Quant Research jobs, the most frequently searched job titles are:

Infographic showing various Commodities Quant Research job openings in the United States as of June 2026, with employment types broken down into 100% As Needed. Highlights an 93% Physical, 4% Hybrid, and 3% Remote job distribution, with an average salary of $119,165 per year, or $57.3 per hour.

Commodities Quant Analyst

Houston, TX • On-site

Verition Group LLC
51 - 200 employees
Learn more about Verition Group LLCexternal

Full-time

Re-posted 19 days ago

Job 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 Global Credit, Global Convertible, Volatility & Capital Structure Arbitrage, Event-Driven Investing, Equity Long/Short & Capital Markets Trading, and Global 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

Apply