DRW
Quantitative Researcher - Commodities
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Quant Researcher – Global Commodities Trading Team – DRW
DRW is a diversified trading firm with over 3 decades of experience, bringing together sophisticated technology and exceptional talent to navigate markets worldwide. Our trading activities use DRW’s own capital at our own risk, enabling rapid placement of laser-focused bets in rapidly evolving circumstances. We value autonomy, transparency and trust, metrics that are at our core.
Headquartered in Chicago with operations across the U.S., Canada, Europe and Asia, we commercialise sophistication in a wide array of asset classes, including:
- Fixed Income
- ETFs
- Equities
- FX
- Commodities
- Energy
Additionally, we have expanded our expertise into non-traditional strategies such as:
- Real Estate
- Venture Capital
- Cryptoassets
We are a place where curiosity, respect and open minds prevail. Our people thrive on pushing boundaries, operating with high integrity, adaptability and a relentless pursuit of innovation—often questioning consensus in data-driven pursuit of superior investment outcomes.
About the Role
We are seeking an experienced Quant Researcher to join our global commodities trading team, supporting alpha generation, research, development, and maintenance of analytical infrastructure.
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Key Responsibilities
Strategy & Alpha Generation
- Develop systematic trading strategies and alpha-generating signals across commodity markets
- Perform quantitative analysis to support trading decisions
Data & Infrastructure
- Enhance data collection procedures, data pipelines, and analytics infrastructure
- Clean, preprocess, and engineer large-scale datasets for research
- Build, validate, deploy, monitor, and update predictive models
- Utilise and advance AI and LLM applications for trading insights
Tooling & Collaboration
- Assist in the development of analytical tools and post-trade diagnostics
- Translate business needs into managed data science projects
- Collaborate with cross-functional stakeholders at all project stages
- Communicate complex findings clearly to both technical and non-technical audiences
Qualifications & Skills
Education & Experience
- Bachelor’s, Master’s, or PhD in mathematics, statistics, physics, engineering, computer science, or a related field
- Minimum of two years of experience in an alpha-generating role
- Hands-on expertise with AI and LLM technologies
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Technical Proficiency
- Data science and engineering (large dataset handling, cleaning, preprocessing, and feature engineering)
- Proficiency in programming and scripting (e.g., Python, R, or other relevant languages)
- Experience with data pipelines, quantitative modelling, and model deployment/monitoring
Soft Skills & Culture Fit
- Demonstrates driving autonomy and delivering impactful results
- Clear communication – both written and verbal – with an ability to translate complex ideas
- Collaborative mindset with a strong outcome orientation
- Respectful, positive, and team-first attitude
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