Data Scientist, Product

About the role

We're redefining how software is built and who gets to build it. Our mission is to achieve Autonomy for All: making programming accessible, collaborative, and powered by AI. To realize this vision, we need people who are obsessed with understanding how users experience our product and can turn that understanding into decisions that move the needle.

Responsibilities

• Design and analyze product experiments to evaluate feature launches, onboarding changes, and in-product interventions with rigorous statistical methodology.
• Own the analytics for core product areas — Growth (activation, engagement, monetization & retention), feature adoption, product quality, AI agent effectiveness, and proactively surface insights that influence product roadmap decisions.
• Build the analytical foundation for Replit's enterprise business, understanding team adoption patterns, workspace collaboration dynamics, and expansion signals that inform go-to-market and product strategy.
• Develop predictive models to forecast frameworks to measure impact of features and new launches on user behavior, including likelihood to retain, convert, or expand, and embed those signals directly into product and growth workflows.

Qualifications

• Bachelor's degree in Computer Science, Statistics, Mathematics, Economics, or related field, OR equivalent real-world experience in data roles.
• 5+ years of experience in data science with a focus on product analytics, growth, or user behavior.
• Strong SQL skills and experience working with large datasets, particularly event-level user behavior data, and designing ETL workflows using dbt.
• Proficiency in Python and data science libraries (pandas, scikit-learn, statsmodels, etc.).
• Experience designing and analyzing A/B tests and experiments, including rigor around sample sizing, power analysis, significance testing, novelty effects, interference between experiments, and causal inference.
• You leverage AI tools extensively in your own analytical workflow and can demonstrate how they make you more effective, while maintaining high standards for output quality.

Preferred Qualifications

• Experience at a PLG company with a self-serve funnel and freemium or usage-based pricing model.
• Experience with modern data stack (dbt, BigQuery, Snowflake, Fivetran, etc.) and product analytics platforms (Amplitude, Mixpanel, Segment, etc.).
• Experience with causal inference methods (difference-in-differences, synthetic control, propensity score matching).
• Experience designing ETL workflows and data pipelines using dbt or similar tools.

Benefits

• Competitive Salary & Equity
• 401(k) Program with a 4% match (US Only)
• Health, Dental, Vision and Life Insurance
• Short Term and Long Term Disability
• Paid Parental, Medical, Caregiver Leave
• Flexible Time Off (FTO) + Holidays
• Social Events
• Wellness Stipend
• Autonomous Work Environment
• In Office Set-Up Reimbursement (In-Office Only)