Investment Data Science Intern (Summer 2027)

Walleye Capital Internships•New York, NY

2d•Onsite

About The Position

Walleye Capital is seeking Investment Data Science Interns for Summer 2027. As an intern, you'll engage in high-impact projects focused on alternative data research supporting long/short discretionary investment strategies. Your work may include developing thematic investment theses, exploring new datasets, or conducting stock-specific analyses. You'll have the opportunity to collaborate with senior professionals, gain hands-on experience with real-world hedge fund data, and enhance your analytical and statistical skills. 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 non-MBA master’s degree in a STEM-related field, with an expected graduation date between December 2027 and June 2028.
Demonstrate strong quantitative and analytical skills, with a solid foundation in programming, statistics, and problem-solving capabilities.
Self-motivated, adaptable, and detail-oriented, with the ability to manage multiple priorities in a fast-paced environment.
Showcase creativity and enthusiasm for leveraging AI tools to enhance productivity and improve processes and workflows.
Thrive in a collaborative culture that values intellectual humility, creativity, and continuous learning.

Responsibilities

Partner with the Central Data Science team on research initiatives, supporting both scalable production insight pipelines and ad hoc analytics to inform investment decisions.
Collaborate with discretionary equity L/S portfolio managers and analysts to understand their investment theses and identify areas where alternative or fundamental data can augment conviction; develop and prototype predictive models or analytics tools that help surface patterns across sectors, tickers, or themes.
Conduct exploratory data analysis (EDA), signal validation, and performance attribution studies using historical and real-time data sets.
Assist in the evaluation and onboarding of new data vendors by performing quantitative and qualitative assessments of potential alpha signals.
Learn and implement core data science and data engineering workflows on the firm’s Cloud and Linux infrastructure.
Clean, transform, and join large structured and unstructured datasets from internal and external sources; maintain reproducibility and robustness through version-controlled code, documentation, and adherence to the team’s development standards; utilize AI to enhance processes and analyses.