Central Equity Quant Research (CEQR) Intern (Summer 2027)

Walleye Capital Internships•New York, NY

1d•$20,000•Onsite

About The Position

Walleye Capital is seeking highly quantitative and analytical interns to join our Central Equity Quant Research (CEQR) team for Summer 2027. As a CEQR intern, you’ll work at the core of our firm’s trading infrastructure, developing and optimizing models that reduce trading costs and decipher short-term alphas. You’ll contribute to projects that influence our quantitative investment strategies and collaborate closely with our investment teams. This is a unique opportunity for quantitative minds who thrive at the intersection of mathematical modeling, data analysis, and programming. The internship is 10 weeks in length and will take place in New York City from June to August 2027.

Requirements

Pursuing an undergraduate or advanced degree in computer science, engineering, statistics, mathematics, or a related field, with an expected graduation date between December 2027 and June 2028.
Demonstrate strong quantitative and analytical skills (including programming proficiency in R and/or Python).
Self-starters who enjoy digging into complex, open-ended problems and can work both independently and collaboratively with a team.
Genuine interest in financial markets, execution trading, systematic investing, AI/LLM application, and using technology in dynamic, data-rich environments.
Creativity and enthusiasm for leveraging AI tools to enhance productivity, improve processes, and generate investment alpha.
Thrive in a collaborative culture that values intellectual humility, creativity, and continuous learning.

Responsibilities

Conduct quantitative research to evaluate model performance and identify opportunities for improvement using large-scale datasets.
Build predictive and explanatory models to identify patterns in asset returns, risks, trading costs and price impact, or other aspects relevant to managing our portfolios, including statistical ranking models, calibration frameworks, and structured approaches to synthesizing unstructured data.
Gain exposure to a range of strategies and collaborate across groups to integrate your work into production systems that support trading decisions.
Help build and enhance our infrastructure and tools for trading, risk management and attribution, leveraging AI tools including LLM-based analytical pipelines.