Quantitative Research Intern
DRW is a Chicago-based diversified trading firm that uses technology, quantitative research, and risk management to provide liquidity across traditional and digital-asset markets.
About DRW
Founded by Don Wilson in 1992, DRW trades for its own account across global markets and operates strategies in cryptoassets, venture capital, real estate, carbon markets, and public-equity investments. Its crypto business, Cumberland, has provided institutional crypto-asset liquidity since 2014.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
Solve challenging trading-environment problems using statistical algorithms, machine learning techniques, and derivatives pricing theory. Analyze market data, develop quantitative models, build research infrastructure, and collaborate with traders and researchers.
Requirements
- Pursuing a Bachelor's, Master's, or PhD in a technical discipline focused on statistics, optimization, machine learning, artificial intelligence, quantitative finance, or a related field
- Graduating between December 2027 and August 2028
- Proficiency in Python and the Python machine learning stack, including NumPy, pandas, and scikit-learn
- Programming experience exploring large datasets
- Strong analytical and problem-solving skills with a solid foundation in statistics
- Working knowledge of probability theory, stochastic calculus, and numerical algorithms
- Excellent written and verbal communication skills
Responsibilities
- Create practical solutions to trading-environment problems
- Conduct statistical analysis of market data, historical trends, and relationships across multiple asset classes
- Formulate and apply mathematical models, quantitative methods, and machine learning techniques to identify trading opportunities
- Build and refine research infrastructure and tools with traders and researchers
Benefits
- Organized social events
- Meaningful projects advised by a trader
- Educational, social, and team-building activities
- Mentorship with an experienced professional
- Options course taught by an experienced trader
- Technology immersion course
