Data Analyst Intern, Stripe

• Enrolled in a quantitative Master's degree program (e.g. Data Analytics, Statistics, Economics, Mathematics, etc.) with the expectation of graduating in winter 2026 or spring/summer 2027
• Experience with a scientific computing language (such as Python, R, etc) and SQL. We believe new programming languages can be learned if the fundamentals and general knowledge are present!
• Experience communicating and collaborating with multidisciplinary stakeholders in a team environment

Desirable

• Data Science at Stripe is a vibrant community where data analysts, data scientists, and engineers learn and grow together
• You will work with some of Stripe’s most fundamental and exciting data, and use that data to help drive company-wide initiatives. We have a variety of Data Analytics roles and teams across Stripe and will seek to align you to the most relevant team based on your background
• Our internship program provides the opportunity to work on meaningful business initiatives that will grow the GDP of the internet
• Through the internship, you will work with many systems and technologies, gain experience in working with large datasets and analytical methodologies/tools to help us better understand our users and build better products
• Each intern has a dedicated mentor, and every intern project is part of the team's roadmap that will directly contribute to Stripe's mission
• As you collaborate with industry experts on initiatives that expand global commerce, you will develop a strong first-hand understanding of the role analytics plays in steering business strategy and results
• We're not just focused on your immediate contributions; we're invested in your growth. Stripe sees this internship as an opportunity to grow your technical expertise and facilitate personal development, preparing you for a career in the tech industry
• Partner closely with Data Scientists, Data Analysts, and business partners to drive business impact through rigorous analytical solutions
• Apply machine learning, causal inference, or advanced analytics on large datasets to: i) measure results and outcomes, ii) identify causal impact and attribution, iii) predict the future performance of users or products, to drive business success
• Influence business actions and strategy by developing actionable insights through metrics and dashboards
• Drive the collection of new data and the refinement of existing data sources
• Learn quickly by asking great questions, finding how to work with your mentor and teammates effectively, and communicating the status of your work clearly
• Present your work to the Data Science team, partner teams, and fellow interns