Quantitative Investment Associate Intern

Program Overview:

The Quantitative Investment Associate Internship is a 10-week program for Master's and PhD candidates, based in our Boston office and running from June through August 2027. You will join an investment team and own one substantial project from framing through delivery. Projects come from live needs across our portfolio management, research, and development teams and are designed to produce work with value beyond the summer; several recent intern projects have been used in production or shaped the research that followed. You will have a manager and support from peers across your team, and you will present your work to the investment teams at the end of the summer.

Projects usually begin as a loosely framed need from a team rather than a specification, so part of the job is defining an answerable question. Your approach may change as the evidence develops and you incorporate input from colleagues. Coding and AI tools are part of how our researchers and developers work, and we expect interns to use them thoughtfully and validate what they produce.

Strong-performing interns may be considered for full-time opportunities across the Investment division, including roles beyond the team they join for the summer.

What You’ll Do:

Our investment process depends on three connected components: research into what predicts returns and risk, an implementation process that carries those findings through to real portfolios, and the technology that supports both. Intern projects can come from any part of that work, and most interns focus on one or two areas over the summer. Recent projects have involved:

• Finding and testing what predicts returns and risk. Developing systematic signals, working with new datasets, and testing whether published findings hold in our own setting.
• Understanding how our risk models behave. Examining the structure and assumptions inside the models we use to measure and forecast risk.
• Turning investment models into live portfolios. Portfolio construction, trading and costs, and the differences that emerge when one strategy is run across many client accounts.
• Building the tools investment teams use. Internal tools and data pipelines, including tools that draw on both firm data and generative AI.
• Modernizing the systems the investment process runs on. Rewriting production code and making research and model updates faster and more repeatable.

We're Looking for Teammates With: 

• Currently enrolled in a Master’s or PhD program in a quantitative discipline (including, but not limited to, statistics, mathematics, economics, financial engineering, computer science, physics, and operations research) with an expected degree completion between December 2027 and June 2028.
• Ability to write the code needed to complete your own work. We work primarily in Python.
• Interest in applying quantitative methods to financial markets.
• Experience carrying an empirical or computational project from an open question through to a finished result, using real data and your own code. Examples might include a thesis or dissertation involving original analysis, a working or published paper, a research assistantship in which you owned a workstream, or a professional project in which you built a tool or model others used.
• Availability for the full 10-week program, which is based in Boston. Interns are expected to work from our Boston office at least four days per week.

The hourly wage for this position is $50.00 per hour for Master’s candidates and $65.00 per hour for PhD candidates. Interns relocating to Boston are eligible for a relocation stipend of $1,000. Applications are reviewed on a rolling basis.