Quantitative Researcher - Prediction Markets

DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk.

Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets.

We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus.

DRW is looking for a Quantitative Researcher to join our growing Prediction Markets team. The team develops systematic trading strategies across a wide range of prediction markets. This role combines quantitative modeling, market data analysis, and strategy development to identify opportunities in rapidly evolving markets. You will work closely with traders and engineers across the full strategy lifecycle, from initial research and model development through production deployment and live performance analysis.

What you’ll do:

• Apply statistical and machine learning methods to develop predictive models and trading signals
• Analyze large and diverse datasets to identify market opportunities and inefficiencies
• Research how short-term signals from related financial markets can improve prediction-market pricing and trading
• Conduct research into pricing, market making, market microstructure, execution, and risk management
• Conduct rigorous quantitative research and evaluate strategies through backtesting and simulation
• Develop analytical tools to monitor performance and improve live strategies
• Collaborate with traders and engineers to translate successful research into production trading systems
• Explore new products, datasets, and approaches as the prediction-markets business expands

What we’re looking for:

• 2+ years of experience in quantitative research, systematic trading, data science, or a related field
• Degree in a quantitative or technical discipline such as mathematics, statistics, computer science, engineering, physics, or economics
• Strong knowledge of probability, statistics, and quantitative modeling
• Experience conducting research with large, noisy, real-world datasets
• Strong programming skills, particularly in Python
• Ability to formulate and independently drive open-ended research problems
• Strong attention to detail and a rigorous approach to testing and validating results
• Ability to communicate complex ideas clearly and work effectively with traders, researchers, and engineers
• Intellectual curiosity and a genuine interest in financial markets and prediction markets

Additional experience that would be helpful:

• Systematic or electronic trading
• High-frequency or short-horizon signal research
• Probabilistic forecasting or machine learning
• Strategy backtesting and performance analysis
• Experience moving quantitative research into live production

The strongest candidates will combine quantitative rigor with practical judgment, intellectual curiosity, and a willingness to take ownership of difficult, open-ended problems.

The annual base salary range for this position is $200,000 to $300,000 depending on the candidate’s experience, qualifications, and relevant skill set. The position is also eligible for an annual discretionary bonus. In addition, DRW offers a comprehensive suite of employee benefits including group medical, pharmacy, dental and vision insurance, 401k (with discretionary employer match), short and long-term disability, life and AD&D insurance, health savings accounts, and flexible spending accounts.

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