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

XML job scraping automation by YubHub