Data Scientist, Product
Analyzes user behavior and product experiments to drive insights for growth, retention, and enterprise strategy at Replit. Requires 5+ years in product analytics, strong SQL/Python skills, and expertise in A/B testing and causal inference.
About the job
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.
Required Skills and Experience
- 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.
- Leverage AI tools extensively in analytical workflow 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) and product analytics platforms (Amplitude, Mixpanel, Segment).
- 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.
Bonus Points
- Built or contributed to AI-powered analytical tools, automation, or novel measurement approaches.
- Experience analyzing freemium or usage-based pricing models.
- Understanding of developer tools, collaborative coding environments, or technical products.
- Experience working directly embedded with product teams in an agile environment.
- Familiarity with customer data platforms (CDPs) and event tracking implementation.
Skills
SQL, Python, pandas, scikit-learn, Statsmodels, dbt, A/B Testing, BigQuery, Snowflake, Amplitude
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