Data Science Intern (Winter 2027)

WHO WE ARE Notion is the collaborative AI workspace where teams and agents think together https://www.youtube.com/watch?v=vkpYpWfEK5s. We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. This internship will take place from January 25 - April 16 and you will need to be able to work out of our SF office during this time. WHAT YOU'LL ACHIEVE: - Conduct data analyses to gain insights about Notion and use these insights to uncover opportunities for improvements in our product and business. - Communicate these insights with actionable recommendations to cross-functional teams (insights are useful, impact is even better!). - Work with cross-functional partners across the product and business to learn about their functions and use data to advance their respective areas. - Create metrics and build dashboards to monitor the growth and health of Notion. - Communicate insights and recommendations effectively to leadership and have an impact on strategic decision-making. QUALIFICATIONS: - Pursuing a bachelor's or master's in a quantitative field such as Economics, Statistics, Applied Math, Engineering, Computer Science, or Natural Sciences. Must graduate before December 2027. - This internship will take place from January 25 - April 16 and you will need to be able to work out of our SF

Department: Early Career; Team: Early Career