Data Science Intern (Summer 2027)
AI in this role
Data Science Intern to work on brokerage data science initiatives including predictive modeling, experimentation, and agentic trading products.
Join us in building the future of finance.
Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading.
About the team + role
We are building an elite team, applying frontier technologies to the world's biggest financial problems. We're looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn't a place for complacency, it's where ambitious people do the best work of their careers. We're a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards.
Brokerage products are the bread and butter of Robinhood. The Brokerage team is fast-paced, dynamic, and deeply collaborative, driving innovation across our suite of brokerage products.
As a Data Scientist Intern on the Brokerage Data Science team, you'll be part of a high-impact, multi-functional group working closely with partners across product, engineering, user research, design, marketing, finance, and operations. Together, you’ll unlock the power of data to shape the future of our brokerage business and deliver outstanding value to our customers.
We’re looking for a dedicated and ambitious graduate student to help us accelerate product growth through world-class experimentation, analysis, and data-informed strategy. Your work will directly influence the roadmap, uncover new opportunities, and improve the trading experience for millions of users.
This role is based in our Menlo Park office(s), with in-person attendance expected at least 3 days per week.
At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams.
What you’ll do
- Partner directly with a current team member on a specific product line (e.g., Agentic Trading, Prediction Markets, Portfolio Margin, Trading Products, Trading Tools, Robinhood Social, Legend, etc).
- Perform deep-dive analyses to identify product growth opportunities and drive improvements in core business metrics.
- Design, plan, implement, and analyze A/B experiments, and conduct causal inference analysis to evaluate product changes.
- Gain expertise in predictive modeling, uplift modeling, causal inference, and experimentation design.
- Define and maintain key product performance metrics; build scalable dashboards to monitor these metrics and advise decision-making.
- Build compelling data visualizations and narratives to effectively communicate insights and recommendations to multi-functional partners, collaborators, and senior leadership.
- Lead and implement large-scale analytics projects to uncover user insights, inform product strategy, and deliver measurable business impact.
- Partner closely with Product, Engineering, Operations, and other multi-functional teams to integrate data-driven decision-making into product and business processes.
- Assist with established methods, standard approaches, and promote a data-informed culture within the organization.
What you bring
- Currently enrolled in a full-time, graduate degree program with an expected graduation date in Winter 2027 or Spring 2028.
- Pursuing a graduate degree in a quantitative field such as mathematics, statistics, engineering or natural science.
- Proven expertise in data science, with a strong background in statistical analysis and machine learning.
- Outstanding problem-solving skills and the ability to think critically and creatively.
- Strong programming skills in Python & SQL, or other relevant languages.
- Experience with data visualization tools and techniques.
- Ability to successfully implement projects and compete in a fast-paced environment.
- Previous experience working in financial technology is preferred.
Base pay for the successful applicant will depend on a variety of job-related factors, which may include education, training, experience, location, business needs, or market demands. The expected hourly range for this role is based on the location where the work will be performed and is aligned to one of 3 compensation zones. For other locations not listed, compensation can be discussed with your recruiter during the interview process.
Zone 1 (Menlo Park, CA; New York, NY; Bellevue, WA; Washington, DC)$44—$44 USDClick here to learn more about our Total Rewards, which vary by region and entity.
If our mission energizes you and you’re ready to build the future of finance, we look forward to seeing your application.
AI Usage Disclosure: Robinhood uses artificial intelligence (AI) tools to support parts of our recruiting process. These tools enhance the efficiency and consistency of our hiring process; however, all hiring decisions are made by our hiring teams.
Robinhood provides equal opportunity for all applicants, offers reasonable accommodations upon request, and complies with applicable equal employment and privacy laws. Inclusion is built into how we hire and work—welcoming different backgrounds, perspectives, and experiences so everyone can do their best. Please review the Privacy Policy for your country of application.
How we rate this
Data Science Intern (Summer 2027) at Robinhood rates 70 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
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Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where data science was part of your work. What did you do?
- Tell me about a project where predictive modeling was part of your work. What did you do?
- Tell me about a project where experimentation was part of your work. What did you do?
- Tell me about a project where causal inference was part of your work. What did you do?
- Tell me about a project where data analysis was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Data Science, Predictive Modeling, Experimentation, Causal Inference, and Data Analysis. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.
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