About the role#
As a Quantitative Research Intern, you will work within a trading environment focused on systematic equity trading or fixed income options. You will collaborate with traders and researchers to solve complex problems using statistical algorithms, machine learning, and derivatives pricing theory. This role involves using custom research infrastructure to simulate, back-test, and validate models for non-latency sensitive investment opportunities and multi-asset class strategies.
What you'll do#
- Create practical solutions for challenges on systematic equity or fixed income options desks.
- Conduct statistical analysis of market data, historical trends, and relationships across asset classes.
- Formulate and apply mathematical modeling, quantitative methods, and machine learning to identify trading opportunities.
- Build and refine research infrastructure and tools in collaboration with the team.
- Participate in an options course and a technology immersion course to understand the intersection of trading and technology.
What you'll need#
- Currently pursuing a Bachelor’s, Master’s, or PhD in a technical field (Statistics, Optimization, Machine Learning, AI, Quantitative Finance, or related) with a graduation date between December 2027 and August 2028.
- Proficiency in Python, specifically the machine learning stack (numpy, pandas, scikit-learn).
- Solid foundation in statistics and strong analytical problem-solving skills.
- Working knowledge of probability theory, stochastic calculus, and numerical algorithms such as Monte Carlo simulation and finite differences.
- Excellent written and verbal communication skills for reporting methodologies and results.
- Experience with large datasets; exposure to Natural Language Processing or High-Performance Computing is a plus.
Location & details#
- Locations: Chicago, Illinois and New York City, New York.
- Term: Summer 2027.
- Modality: On-site.
- Employment: Full-time internship.
- Support: Includes mentorship, educational activities, and fully furnished housing.
