Job Description

Quantitative Researcher Intern

We are looking for Quantitative Researcher Interns to join our Research group. We are a collaborative, data-driven, intellectually rigorous team responsible for coming up with investment ideas, codifying those ideas into signals, back-testing the signals, and producing return, risk and trading cost forecasts based on the signals to drive trading decisions. We maintain a friendly, team-oriented environment and place a high value on professionalism, attitude and initiative.

As a Quantitative Researcher Intern, you will be immersed in our research effort, working side-by-side with members of the Research group. Our intern program combines theory, practice and technology and provides significant insights into quantitative investment management. You will work on high impact projects that may involve finance, data science, applied math, optimization theory and computer programming.

Typical responsibilities include:

• Performing statistical analysis across large complex data sets from a variety of structured and unstructured sources
• Researching predictable patterns in asset returns, risks, trading costs and other data relevant to financial markets
• Performing portfolio construction research using our proprietary simulation capability
• Conduct research projects from initial stages through analysis, and present directly to the team and stakeholders

Qualifications:

• Enrolled in an undergraduate or graduate program from an educational institution in finance, mathematics, economics, or a closely related discipline emphasizing quantitative or financial analysis. Expected degree completion within a year of the internship.
• Demonstrated academic success
• Understanding probability, statistics, linear regression, time-series analysis, linear algebra, calculus, optimization and portfolio theory
• Experience with a statistical computing environment such as Python, R, STATA, or MATLAB
• Experience leveraging large language models (LLMs) and coding agents to support research and programming workflows is a plus
• Knowledge of the application of statistics to economics (including econometrics or regression analysis)
• Experience analyzing large data sets
• Passion for financial markets
• Ability to communicate complex empirical research findings and conclusions clearly, including through effective use of data visualizations
• High energy and strong work ethic

The weekly wage range for this position is $3,500 - $5,000 per week.

Arrowstreet Capital operates a robust talent acquisition program, and we also seek to compensate and reward our employees competitively within our industry and in line with our merit-based culture. The determination of a successful candidate's base wage placement within the listed range will vary based on the candidate's relevant experience and qualifications (which may also include relevant certifications, credentials and other education), the job responsibilities and scope, the commensurate resulting level of the position and other relevant factors. The listed range is also an estimate, and additional information regarding base wages and other elements of total compensation offered by Arrowstreet Capital to successful applicants will be communicated during the recruitment process.

Arrowstreet Capital is a Boston-based systematic investment firm that manages global equity portfolios for institutional investors around the world.

All qualified applicants will receive consideration for employment without regard to sex, race, color, religion, national origin, ancestry, genetic information, age, pregnancy, medical condition, disability, veteran or military status, marital status or any other characteristic protected by federal, state, or local law.

Arrowstreet Capital is committed to working with and providing reasonable accommodations for qualified individuals with disabilities and disabled veterans. If you need a reasonable accommodation for any part of the employment process due to a disability, contact us to discuss the nature of your request and contact information.

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