Data Scientist

Who you are

• 6+ years in data science, with significant time on growth or experimentation for high-scale prosumer, PLG, or self-serve products
• Data science experience at a fast-growing startup, where you built metrics, datasets, and experimentation practices without much existing infrastructure
• Deep expertise in experimental design and statistical inference, including reaching reliable decisions when readout windows are short and the outcomes that matter are slow
• Experience establishing experimentation standards or platforms adopted by multiple teams
• Expert SQL and Python
• A track record of analysis that changed what a team shipped, and of influencing senior Product and Engineering leaders
• Heavy, practical use of AI tools to move faster in your own work
• Comfortable building your own datasets in dbt
• Pricing, packaging, or monetization analysis for usage- or credit-based products
• International or mobile growth experience
• MS or PhD in statistics, economics, computer science, or another quantitative field
• Experience with multi-armed bandits or adaptive experimentation
• Familiarity with developer tools, AI products, or creator platforms
• We welcome your unique perspective and experiences in shaping this product. We encourage people from all kinds of backgrounds to apply, including and especially candidates from underrepresented and non-traditional backgrounds

What the job involves

• You'll be one of the founding data scientist on Replit's Growth team, working with Product and Engineering leadership across acquisition, activation and recommender systems, and helping shape how Replit experiments
• This role is for someone who doesn't wait to be asked. You spot problems and opportunities before anyone else does, bring a strong point of view, and push it until it changes what we build
• Own data science for major growth areas, partnering with PMs and engineers from problem framing and sizing through launch and readout
• Make fast decisions trustworthy: we ship weekly and need a decision within days, but retention takes weeks to show up. You'll design the experiments and metrics that close that gap; for example, variance reduction (CUPED), sequential testing, and short-term proxy metrics validated against long-term retention and revenue
• Help set the experimentation standards teams rely on for Replit's highest-traffic surfaces: how metrics and guardrails are defined, and the checks that catch a broken test before it misleads anyone
• Use quasi-experimental designs (difference-in-differences, synthetic control, regression discontinuity) where randomization isn't feasible, such as pricing changes and regional launches
• Help define the data science behind an emerging personalization and recommendations workstream: problem framing, offline and online evaluation, and measuring incremental lift
• Model the economics of a freemium, usage-based product: credit consumption, conversion, and how pricing and limits change behavior
• Develop user and project segmentation from behavioral and content signals (e.g., embeddings and clustering) so growth analysis reflects what people are actually building
• Partner with Data Engineering on a shared metrics layer and experimentation tooling

Benefits

• Remote-First and Autonomous Working Environment
• Flexible Work Hours
• Equity
• Home Office Set-Up Stipend
• Health, Dental, Vision, and Life Insurance
• Short Term and Long Term Disability
• Monthly Expenses Stipend
• Commuter Benefits
• Parental and Baby Bonding Leave
• Flexible PTO (2 Weeks Minimum Required) + Holidays
• 401k Program
• Annual Company/Team Offsites (4/year)