Data Scientist

Replit is redefining how software is built and who gets to build it. Our mission is Autonomy for All , making programming accessible, collaborative, and powered by AI.

This role owns how Replit understands its customers across every touchpoint. You'll build the analytics and intelligence layer that spans marketing performance, customer signals, and support , turning massive volumes of behavioural data, feedback, and interaction signals into insights that drive growth, retention, and revenue.

You will:

• Design and analyse marketing experiments across paid, lifecycle, and content channels; optimise CAC, LTV, and ROAS
• Build multi-touch attribution and marketing mix models to understand what's driving growth
• Synthesise customer signals , support tickets, social, reviews, CSAT , into automated intelligence that reaches the teams who need it
• Build churn and retention models to identify at-risk users and inform lifecycle intervention strategies
• Define and maintain customer segmentations and personas that drive targeting, messaging, and product decisions
• Build the analytical foundation for Voice of the Customer , connecting qualitative feedback signals to quantitative behaviour data at scale
• Detect emerging product issues and bugs faster by surfacing support signal early enough to shape engineering priorities
• Optimise automation and deflection to reduce support load and improve self-serve resolution rates
• Build the measurement foundation to fully optimise ROI across all support activities
• Use LLMs and agentic workflows to analyse unstructured data at scale and automate recurring analysis
• Create automated reporting that puts key metrics to inform the company

Required Skills and Experience:

• 6+ years of experience in data science with a focus on marketing, growth, or customer analytics
• Strong SQL skills and experience with large-scale event-level user behaviour data; experience designing ETL workflows using dbt
• Proficiency in Python and data science libraries (pandas, scikit-learn, statsmodels, etc.)
• Experience designing and analysing A/B tests with statistical rigor (sample sizing, significance testing, causal inference)
• Experience building dashboards and visualisations (Hex, Looker, Tableau, Mode, or similar) , ideally automating them
• Demonstrated experience using LLMs/AI tools in analytics workflows , not just prompting, but building automated systems
• Track record of partnering cross-functionally with Marketing, Product, Engineering, Support, and Revenue/Sales teams , not just serving a single stakeholder

Preferred Qualifications:

• Experience with modern data stack (dbt, BigQuery, Snowflake, Fivetran, Segment, etc.)
• Background in growth analytics, marketing analytics, or conversion rate optimisation at a SaaS or PLG company
• Experience with marketing technology platforms (Google Analytics, Segment, Iterable, Salesforce)
• Experience with attribution modelling, marketing mix modelling, or incrementality testing
• Experience analysing unstructured customer data (support tickets, reviews, social mentions) using NLP or LLM-based approaches
• Understanding of PLG motions and self-serve conversion funnels
• Experience with support analytics, CSAT analysis, or customer experience measurement

Bonus Points:

• Experience analysing freemium or usage-based pricing models
• Understanding of developer tools, collaborative coding environments, or technical products
• Experience with causal inference methods (difference-in-differences, synthetic control, propensity score matching)
• Experience building AI agents or automated analytical pipelines using LLM APIs