Quantitative Developer Intern, Summer 2027

Summary

Arrowstreet Capital, Limited Partnership is a Boston-based systematic investment firm that manages global equity portfolios for institutional investors around the world. They are looking for Quantitative Developer Interns to join their Research team, where the role involves solving complex quantitative problems and enhancing investment strategies through collaboration with Quant Researchers and Developers.

Responsibilities

• Solving complex quantitative problems with Python or R
• Designing and developing tools or libraries to enhance our data science technology stack
• Performing exploratory data analysis across large complex data sets to inform investment and signal ideas
• Implementing performance improvements in our data analysis and numerical programming libraries
• Running POCs to evaluate technologies and libraries in cloud and PyData ecosystems

Skills

• Enrolled in an undergraduate or graduate program from an educational institution in a technical field, such as computer science or engineering, with an additional focus in data science, applied mathematics, economics. Expected degree completion within a year of the internship
• Strong analytical, quantitative, programming and problems solving skills
• Knowledge of software design paradigms, data structures, and numerical algorithms
• Understanding of probability and statistics, including linear regression and time-series analysis
• Excellent communication and collaboration skills
• Interest in financial markets (prior experience not required)

Qualifications

Must Haves

• Enrolled in an undergraduate or graduate program from an educational institution in a technical field, such as computer science or engineering, with an additional focus in data science, applied mathematics, economics. Expected degree completion within a year of the internship
• Strong analytical, quantitative, programming and problems solving skills
• Knowledge of software design paradigms, data structures, and numerical algorithms
• Understanding of probability and statistics, including linear regression and time-series analysis
• Excellent communication and collaboration skills
• Interest in financial markets (prior experience not required)