PeopleX Insights & Analytics Intern (Summer 2027)

Robinhood

Menlo Park (CA)

On-site

USD 44,000 - 61,000

Full time

7 days ago
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Benefits offered by this job

Market pay
Lifestyle wallet
AI tools access
Paid time off
Catered meals & commuter benefits

Job summary

Robinhood is seeking a PeopleX Insights & Analytics Intern for Summer 2027 in Menlo Park, CA. You will design and build data products that inform talent strategy, analyze retention and team performance, and apply language models to meaningful, mentorship-guided projects.

The role emphasizes real-time insights, cross-functional collaboration, and in-person work at least 3 days per week in the Menlo Park office.

Qualifications

  • Pursuing a graduate degree in a quantitative field with expected graduation Winter 2027/Summer 2028.
  • Strong SQL and Python/R skills with demonstrated ability to draw insights from data.
  • Curious and excited about a fast-paced, learning-focused environment with teamwork.

Responsibilities

  • Develop and refine predictive models to forecast workforce trends.
  • Build and maintain automated data pipelines to transform raw people data into real-time insights using SQL/dbt.
  • Design scientifically-backed survey methodologies and employee listening strategies.

Skills

SQL
Python/R
Data visualization
Communication

Education

Graduate degree in Data Science

Tools

Workday
Slack
Google Suite

Job description

PeopleX Insights & Analytics Intern (Summer 2027)
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.

The Talent Management & Analytics team within our PeopleX organization is building the next generation of data tools, integrating advanced predictive insights and AI into our workforce systems. We create the data solutions that help the company recruit great talent, build high-performing teams, and put real-time insights into the hands of decision-makers. At the intersection of data science, product development, and organizational psychology, we're changing how Robinhood uses data to support our employees and forecast organizational needs.

As a PeopleX Insights & Analytics Intern, you'll work with our team to design and build high-impact data products that our leaders and managers rely on. You'll contribute to analyses that help us understand what allows talent to thrive, how to accelerate team performance, and how to build better retention strategies. This is a unique opportunity to apply cutting-edge language models and predictive analytics to meaningful work under the mentorship of a data scientist and our talent management team.

This role is based in our Menlo Park, CA office 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
  • Develop and refine predictive models to forecast workforce trends, such as attrition risk and hiring velocity.
  • Build and maintain automated data pipelines to transform raw people data into reliable, real-time insights using SQL and dbt.
  • Support the design of scientifically-backed survey methodologies and "always-on" employee listening strategies to surface actionable organizational health signals.
  • Create high-fidelity visualizations and dashboards that translate complex organizational data into clear, executive-ready insights.
  • Collaborate with the team on AI-driven workflows to automate the analysis and summarization of unstructured feedback and internal documentation.
  • Ensure data integrity by defining metric dictionaries and maintaining a robust semantic layer for core People KPIs.
What you bring
  • Pursuing a graduate degree in Data Science, Statistics, Computer Science, Economics, or a related quantitative field with an expected graduation date of Winter 2027/Summer 2028. Preference for related work experience in HR (prior internship(s), co-op roles, etc)
  • Strong proficiency in SQL and Python/R for data manipulation and statistical analysis, with a portfolio or projects showcasing your ability to draw insights from complex datasets.
  • You’re curious and excited about a fast-paced work environment centered on learning and contributing to the business
  • You’re organized and detail‑oriented with a knack for project coordination
  • You have strong written and verbal communication skills and thrive in team collaboration
  • Familiarity with tools like Workday, Slack, and the Google Suite are a plus

What we offer

  • Market competitive compensation structure
  • Quarterly lifestyle wallet for personal wellness, learning and development, and more!
  • Access to the best AI tools on the market and continuous AI skill-building for every employee, technical or not
  • Time away including company holidays, paid time off, and sick time!
  • Lively office environment with catered meals, fully stocked kitchens, and geo‑specific commuter benefits

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)

$38 - $38 USD

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 thePrivacy Policy for your country of application.

Equal Employment Opportunity Information

At Robinhood, we care deeply about diverse representation in our workforce as it supports our mission to democratize finance for all. In support of this goal, we encourage applicants to voluntarily identify demographic information. This information helps us to continue building a more inclusive workplace and to ensure effective recruiting programs that are inclusive of individuals across all backgrounds.

Self-identifying in this section is completely voluntary and if you choose not to provide any information, please select the “I don't wish to answer” option under that question. Whatever your decision, data that you provide in this section will not be considered in the hiring process or thereafter. Individuals seeking employment at Robinhood are considered without regard to race, color, religion, national origin, age, sex, sexual orientation, marital status, ancestry, physical or mental disability, neurodivergence, veteran status, gender identity or expression, or any other characteristic protected by law.

You are being given the opportunity to provide the following information in order to help us comply with federal and state Equal Employment Opportunity recordkeeping, reporting, and other legal requirements, and to be used in our efforts to recruit a diverse workforce. Any information that you do provide will be recorded and maintained in a confidential manner. For more information on EEOC definitions, please reference this document .

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