Job OverviewWe are looking for Quantitative Developer Interns to join our Research team. We are a collaborative, data-driven, intellectually rigorous group responsible for proposing investment ideas, codifying these ideas into signals, and back-testing these signals to produce return, risk and trading cost forecasts to drive trading decisions. We work in a friendly environment and place a high value on learning, innovation, attitude and initiative.
Our Quantitative Developers are responsible for delivering impact projects using cloud technologies, AI, distributed and high-performance compute, numeric computation, data visualization and APIs to solve complex problems in finance and research.
As a Quantitative Developer Intern, you will be immersed in our research efforts, working closely with Quant Researcher and Quant Developers to enhance our investment strategies. Our internship program combines theory and practice, providing experience delivering real-world projects in quantitative finance and technology.
ResponsibilitiesTypical responsibilities include:
- 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
Qualifications
- 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
- Experience with distributed computing, natural language processing, AI / machine learning, library development, system design, numeric processing or data visualization
- Creativity and enthusiasm leveraging technologies including AI to enhance productivity, automate processes and improve technical quality
- Excellent communication and collaboration skills
- Interest in financial markets (prior experience not required)
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.
