Quantitative Researcher Intern
At a glance
Junior Data Science role at Point72. New York · full-time · $120,000–$180,000 base.
dataroles summary, based on the employer's posting.
What you'll do
- Develop equity-trading signals through research, implementation, backtesting and possible use
- Adapt machine-learning findings or conduct original research to create signals that could improve portfolio returns
- Analyze large datasets and identify features that can inform predictive models
- Support the research team and help strengthen its research infrastructure
What you bring
- You are pursuing a master’s or doctorate in machine learning, computer science, finance, mathematics or another quantitative discipline
- You have independently researched machine learning with large, potentially noisy datasets
- You can program in Python or C++ and work in a Linux environment
Who this fits
This internship suits a graduate student who can take ownership of research while working both independently and with teammates. Internships are offered for Fall 2026, Spring 2027 and Summer 2027.
From the employer
JOB RESPONSIBILITIES
A highly collaborative, fast-growing team, Point72 Internal Alpha Capture (IAC) is developing scalable quantitative equity trading signals that leverage rigorous research, state-of-the-art machine learning methods, a broad range of public and proprietary data sources, and unparalleled computing power.
We are looking for exceptional students to join us as quantitative researcher interns for Fall 2026, Spring 2027 and Summer 2027. Our interns will work closely with our team, receive comprehensive, in-depth training, and help develop novel signals that may have real impact.
You will gain exposure to a variety of activities, which may include:
- Conducting full pipeline signal research, from ideation, via implementation and backtesting, to eventual application.
- Adapting and extending existing results in the broad field of machine learning; conducting novel research as needed to potentially develop new signals that may enhance portfolio returns.
- Analyzing very large data sets to extract features useful for predictive models.
- Providing research assistance to the team.
- Helping improve the team’s research infrastructure.
DESIRABLE CANDIDATES
- Masters or PhD candidates in machine learning, computer science, finance, mathematics, or other quantitative disciplines.
- Demonstrated ability to conduct independent research utilizing machine learning over large, possibly noisy, data sets.
- Strong analytical and quantitative skills, and detail-oriented mindset.
- Proficient in Python or C++, and Linux environment.
- Excellent written and verbal communication skills, willing to proactively engage other team members in helping to foster a highly collaborative, team-oriented research environment.
- Willing to take ownership of his/her work, working both independently and within a collaborative team.
- Prior experience in the financial services industry is not required.
- Commitment to the highest ethical standards.
The annual base salary range is $120000.00-$180000.00 (USD). Actual compensation offered to candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level among other things. Details about eligibility for bonus compensation (if applicable) will be finalized at the time of offer.
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