Data Scientist Intern - 2027
Hudson River Trading·New York·United States·Hedge Fund & Quant
Hudson River Trading is hiring a Data Scientist Intern - 2027 in New York. Posted 2026-09-22; applications close 2026-11-21 (in 56 days).
Role details
Data Science Summer Internship Program
Hudson River Trading (HRT) is seeking highly motivated full-time students to join our Data Science Summer Internship Program. Data is a cornerstone of HRT’s trading strategies, serving as the raw fuel that powers research, automated trading, and risk management. While Algorithm Developers focus on statistical modeling and Software Engineers focus on the systems that power our trading, HRT Data Scientists focus on extracting useful information from the vast volume of data available in the world. Data Scientists are responsible for normalizing and validating vendor data, extracting features from quantitative and textual data, applying rigorous quality checks, and investigating methodologies for providing the highest quality data for research and trading.
What to Expect
- A hands-on introduction to data, modeling, and engineering practices in the algorithmic trading industry.
- Independent data investigation projects in Python using open-source libraries such as pandas and polars.
- Opportunities to learn about HRT's research and trading infrastructure across all areas.
- Technical project work and mentorship, offering a deeper understanding of global financial markets.
- Opportunities to connect with fellow interns, participate in team events, and explore the unique culture and experiences at each HRT office location.
Qualifications
- Currently a full-time student pursuing a degree in a STEM field (a computer science background is not required).
- Programming experience with Python at the level of "Python for Data Analysis" by Wes McKinney.
- A genuine curiosity for working with data and finding insights.
- Independent data projects or participation in Kaggle competitions are a plus.
- Exceptional attention to detail.
- Strong communication skills.
Compensation and Application Notes
Weekly base salary of $5,800, in addition to company-paid housing, meals, and other perks.
Note: We do not allow multiple applications. Please apply to the ONE role you are most interested in, and we will consider you for all open positions during the review process.
Culture at HRT
Hudson River Trading (HRT) brings a scientific approach to trading financial products, utilizing one of the world's most sophisticated computing environments for research and development. Our researchers are at the forefront of innovation in algorithmic trading.
At HRT, we welcome expertise from various disciplines, including mathematics, computer science, physics, engineering, media, and tech. We foster a community of self-starters motivated by the excitement of being at the cutting edge of automation in every part of our organization—from trading to business operations and beyond. We celebrate great ideas, regardless of whether they come from veterans or new hires. At HRT, we are friends and colleagues, sharing meals, playing games, or writing elegant code. We embrace a culture of togetherness that extends far beyond the office.
Our goal is to find the best people and bring them together to do great work in a place where everyone is valued. HRT is proud of its diverse staff across global offices and benefits from varied perspectives. HRT is an equal opportunity employer, and we encourage everyone to apply.
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Applying to this role
This Data Scientist Intern - 2027 role at Hudson River Trading runs through the firm's own careers portal and expects a CV and cover letter written specifically for the posting, not a portable submission carried across firms. Jorb AI's application agent tailors a CV and cover letter from your background to this posting and tracks the role alongside the rest of your applications.
Jorb AI tracks details for Data Scientist Intern - 2027 at Hudson River Trading. Postings refresh hourly from primary careers pages. Job details mirror the firm's posting; the apply link goes directly to the source. Last refreshed 2026-09-26.
