Data Science Intern

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.
• Currently pursuing a BA/BS or graduate degree in a quantitative discipline (e.g., Math, Statistics, Physics, Computer Science, Economics) or equivalent experience.
• Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.

Req ID: P78149

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