Want to get hired at Notion?

Data Scientist, Product

Notion

San Francisco, CAOn Site

Original Job Summary

About Notion

Notion helps you build beautiful tools for your life’s work by connecting docs, notes, projects, calendar, and email, all with AI built in to find answers and automate work. Trusted by millions including organizations like Toyota, Figma, and OpenAI.

About The Role

As a Data Scientist, Product at Notion, you will work closely with product, engineering, and marketing teams to transform raw data into actionable insights. You will be involved in defining key metrics, running experiments, and developing dashboards that drive product decisions.

What You'll Achieve

  • Apply expertise in statistical inference and data analysis.
  • Define problems and opportunities for new projects.
  • Design experiments and evaluate feature success.
  • Collaborate with product, engineering, and marketing teams.
  • Create key dashboards for monitoring progress.

Skills & Requirements

  • Proven experience as a data scientist partnering with product and engineering.
  • Expertise in SQL and a scripting language like Python or R.
  • Strong background in statistical inference, experimentation, and predictive modeling.
  • Ability to transform raw data into actionable datasets.
  • Comfort with balancing speed and accuracy in execution.

Key skills/competency

Data Analysis, Statistical Inference, SQL, Python, R, Experimentation, Predictive Modeling, Dashboarding, Collaboration, Problem-Solving

How to Get Hired at Notion

🎯 Tips for Getting Hired

  • Customize your resume: Tailor your data science experiences.
  • Showcase relevant projects: Highlight predictive modeling examples.
  • Practice SQL/Python skills: Prepare for technical assessments.
  • Study Notion culture: Understand their mission and values.

📝 Interview Preparation Advice

Technical Preparation

Review SQL queries and optimization techniques.
Practice Python/R scripting exercises.
Study statistical inference and modeling cases.
Develop sample dashboards and experiment designs.

Behavioral Questions

Describe a time you solved a data challenge.
Explain a cross-team collaboration success story.
Discuss handling ambiguous project requirements.
Share a decision-making process in experimentation.