Ready to do the most impactful work of your career? At Coinbase, we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase.
This is a 12-week internship during summer 2027.
As a Data Science Intern on the Strategy, Execution, & Analytics team within the Platform group, you'll partner with product and engineering teams to turn data into decisions that drive real business impact. This team builds analytics models and systems that scale insights across Coinbase and directly into the product. You'll collaborate with senior data scientists and business partners to design experiments, build models, and deliver data-driven recommendations that shape how millions of customers experience crypto. You will gain hands-on experience at a publicly traded crypto-native company, with mentorship from senior data scientists and direct exposure to how data shapes the company.
What you'll do:
- Collaborate with product teams to create analyses and build models that drive measurable business outcomes.
- Support the design and execution of experiments, including A/B tests and causal inference methods.
- Build and maintain analytical datasets and pipelines that ensure data integrity and power your analyses and models.
- Distill complex analyses into clear, actionable insights through data-driven storytelling for technical and non-technical audiences.
- Partner with senior team members on analytical deep dives to diagnose and address complex business problems.
Required Skills and Experience:
- Coursework or project experience in statistical modeling, data analysis, or a related quantitative field (e.g., mathematics, economics, physics, computer science).
- Familiarity with SQL for data analysis and Python for programming or modeling.
- Demonstrated interest in experimentation (A/B testing), causal inference, or machine learning through coursework or projects.
