Summer Quantitative Research Internship

About Our Firm

Cubist Systematic Strategies, an affiliate of Point
72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.

KEPL is a fast-growing team at Cubist Systematic Strategies. We specialize in trading medium-frequency statistical arbitrage strategies with high Sharpe. The team is made up of people from top universities and top tier trading and tech firms. We have an open and collaborative culture, and we value rigorous research and innovative technologies.

We are looking for exceptional students to be our quantitative researcher interns for the summer of 2027. An ideal candidate should have a strong passion and initiative to work in a start‑up environment. They should have strong analytical skills and be able to solve hard problems rigorously. Our typical intern candidates come from quantitative PhD programs of top US universities.

Our internship program offers unique KEPL experience. During the internship, our interns will receive rigorous and comprehensive trainings. They will develop strong research skills through working closely with our full-time researchers on brand new quant trading models with real‑world impact. We will consider full‑time offers for interns after the internship.

• PhD candidate in math/physics/statistics/EE/CS, or other quantitative fields
• Strong knowledge of computational math, probability, and statistics
• Strong analytical skills, with attention to details
• Good communication skills
• Willing to work in a fast‑paced start‑up environment
• Willing to learn and to take ownership
• Strong programming skills in Python or C/C++
• Commitment to the highest ethical standards

The annual base salary is $240,000-$300,000 (USD) which will be prorated based on internship start and end date. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.