Quant Researcher Summer Intern 2025 - College Fair Applicants

Position: Quant Research Summer Intern 2025

Location: Boston

Firm Overview

Founded in 2005, Walleye Capital LLC is a global multi-strategy investment firm founded in Minnesota and headquartered in New York City. With over $5.3 billion under management, Walleye Capital currently employs over 350 people and maintains additional seven offices in the United States, including Boston. Our investment approach is rooted in an intellectually honest assessment of what role we play in this industry – constantly testing our assumptions of where we have edge and how we adding value. 

Our approach helps us achieve our continued goal of building a best-in-class, mid-sized multi-strategy hedge fund utilizing robust infrastructure, sophisticated technology, and skilled people to develop an investment business comprised of high-quality implementations of uncorrelated strategies trading across the globe and in multiple asset classes. Importantly, we expand the scope of our investment activities to encompass volatility, fundamental equities, quant, and macro. We invest through a single, centrally managed investment team which affords us the greatest flexibility in opportunistically and quickly deploying capital.

Role Overview

Walleye Capital is hiring a Quantitative Researcher Intern to work in our systematic strategies group Quantic in Boston. We are a tight-knit, collaborative, and intellectually rigorous team responsible for managing a number of systematic trading strategies in equity statistical arbitrage, volatility arbitrage, and futures. We are looking for talented coders who can rapidly prototype and test improvements to our quantitative investment strategies. You will join a team where your creativity, initiative, and teamwork will make direct impacts on trading profits.

What will you do?

• Work on 1-3 specific coding projects for the duration of the internship across many stages of the investment process.
• Partner with team members to build and improve our infrastructure and tools for trading, risk management and attribution.
• Extract and analyze large amounts of historical data from a variety of structured and unstructured sources.
• Design and test new predictive signals, data sets or trading strategies.
• Build machine learning systems used to predict patterns in asset returns, risks, trading costs, or other aspects relevant to managing our portfolios.
• Significant coding in Python and/or R.

What are you like?

• Demonstrated programming proficiency, particularly in R and/or Python.
• Pursuing a bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, or a similar discipline.
• An independent thinker who can build creative approaches to complex problems and articulate those ideas clearly through verbal, written, and visual media.
• Strong quantitative, analytical, and programming skills; preferably demonstrated by real-world research projects and/or code repositories.
• Experience with databases and query languages preferred.
• Passionate about financial markets, investing, and trading.