This is a 12-week internship during summer 2026.

As a Data Science intern and part of the Strategy, Execution, & Analytics team, you’ll spend part of your time collaborating closely with business partners in product and engineering teams — to ensure we’re focused on the biggest opportunities and interpreting our data correctly. You’ll also work with the data engineering team to build analytics models and systems that help scale our insights more broadly, both throughout the company and directly in the product. We expect you to demonstrate clear communication, a strong desire to execute, and best-in-class craftsmanship.

What you’ll be doing (ie. job duties):

• Collaborate with product teams to create analyses and build models to drive positive business impact.
• Assist in designing and conducting experiments.
• Support the team in measuring business performance and help refine core metrics.
• Practice data-driven storytelling, distilling complex analyses into clear, actionable insights.
• Participate in analytical deep dives alongside senior team members to understand and address complex business problems.
• Assist in the development and maintenance of data pipelines, ensuring data integrity and accuracy.

What we look for in you (ie. job requirements):

• Some experience or coursework in statistical modeling, data analysis, or other related quantitative field (e.g., hard science, economics, math, etc.).
• Basic understanding of statistical concepts and a keen interest in furthering this knowledge (in A|B testing, causal inference, ML, etc.).
• Familiarity with data analysis using SQL.
• Some experience or coursework in programming/modeling, preferably in Python.
• An embodiment of our core cultural values: clear communication, positive energy, continuous learning, and efficient execution.

Nice to haves:

• Currently pursuing a BA/BS degree in a quantitative field (ex Math, Stats, Physics, or Computer Science).
• Exposure or interest in data engineering.
• Eagerness to delve into varying levels of data work to understand and improve foundational data structures.

Position ID:  P73390