Quantitative Investment Internship Program - Summer 2027

Acadian Asset Management•Boston, MA

20h•$50 - $65•Hybrid

About The Position

Acadian Asset Management is a global, systematic investment manager that has been at the forefront of data-driven investing since 1986. Headquartered in Boston, with additional offices in Singapore, London, and Sydney, the firm manages over $232 billion for leading institutions worldwide. Acadian utilizes advanced technology, extensive datasets, and multidisciplinary expertise to help clients navigate complex markets and uncover insights that traditional approaches might miss. The company culture is collaborative and intellectually curious, encouraging the testing of ideas, welcoming diverse perspectives, and fostering innovation. The overarching goal is to deliver effective client outcomes and support colleagues in challenging and rewarding work. Acadian offers a flexible hybrid work environment, comprehensive benefits, and a casual yet focused office culture designed to support meaningful, collaborative work.

Requirements

Currently enrolled in a Master's or PhD program in a quantitative discipline (e.g., statistics, mathematics, economics, financial engineering, computer science, physics, operations research).
Expected degree completion between December 2027 and June 2028.
Ability to write code to complete 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 own code (e.g., thesis, dissertation, research assistantship, professional project).
Availability for the full 10-week program (June-August 2027).
Expected to work from the Boston office at least four days per week.

Responsibilities

Join an investment team and own one substantial project from framing through delivery.
Define an answerable question for projects that often begin as loosely framed needs.
Adapt project approach based on developing evidence and input from colleagues.
Use coding and AI tools thoughtfully and validate produced work.
Present project work to investment teams at the end of the summer.
Conduct research into factors that predict returns and risk.
Develop systematic signals and test published findings in Acadian's setting.
Examine the structure and assumptions within risk models.
Contribute to portfolio construction, trading, and cost analysis.
Build internal tools and data pipelines, potentially drawing on firm data and generative AI.
Modernize systems supporting the investment process, including rewriting production code and improving the speed and repeatability of research and model updates.