$210,000 – $350,000
Listed on Replit’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
Replit is looking for a data scientist to drive product decisions through rigorous analysis of user behavior, experimentation, and predictive modeling. The role suits someone who can move fast without compromising quality, design complex experiments, and surface insights that shape the product roadmap across growth, adoption, and enterprise segments.
Our summary, not Replit’s wording. The full posting is on their site.
Skills this role names
- A/B Testing
- Amplitude
- Dialectical Behavior Therapy (DBT)
- Google BigQuery
- Mixpanel
- Pandas
- Python
- scikit-learn
- Segment
- Snowflake
- SQL
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What they ask for
Required
- Bachelor's degree in Computer Science, Statistics, Mathematics, Economics, or equivalent real-world data experience
- 5+ years of data science experience focused on product analytics, growth, or user behavior
- Strong SQL and experience with large event-level user behavior datasets and ETL workflows using dbt
- Proficiency in Python and data science libraries
- Experience designing and analyzing A/B tests with rigor around sample sizing, power analysis, significance testing, and causal inference
- Demonstrated ability to leverage AI tools effectively in analytical work while maintaining output quality
Nice to have
- Experience at a product-led growth company with self-serve funnel and freemium or usage-based pricing
- Experience with modern data stack tools and product analytics platforms
- Knowledge of causal inference methods like difference-in-differences, synthetic control, or propensity score matching
- Experience designing ETL workflows with dbt or similar tools
- Background building or contributing to AI-powered analytical tools
- Understanding of developer tools, collaborative coding environments, or technical products
- Experience working embedded with product teams in agile environments
- Familiarity with customer data platforms and event tracking implementation