Data Scientist

Responsibilities

• Design and analyze marketing experiments across paid, lifecycle, and content channels; optimize CAC, LTV, and ROAS
• Build multi-touch attribution and marketing mix models to understand what's driving growth
• Synthesize 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 behavior data at scale
• Detect emerging product issues and bugs faster by surfacing support signal early enough to shape engineering priorities
• Optimize automation and deflection to reduce support load and improve self-serve resolution rates
• Build the measurement foundation to fully optimize ROI across all support activities
• Use LLMs and agentic workflows to analyze unstructured data at scale and automate recurring analysis
• Create automated reporting that put 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 behavior data; experience designing ETL workflows using dbt
• Proficiency in Python and data science libraries (pandas, scikit-learn, statsmodels, etc.)
• Experience designing and analyzing A/B tests with statistical rigor (sample sizing, significance testing, causal inference)
• Experience building dashboards and visualizations (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

Preferred Qualifications

• Experience with modern data stack (dbt, BigQuery, Snowflake, Fivetran, Segment, etc.)
• Background in growth analytics, marketing analytics, or conversion rate optimization at a SaaS or PLG company
• Experience with marketing technology platforms (Google Analytics, Segment, Iterable, Salesforce)
• Experience with attribution modeling, marketing mix modeling, or incrementality testing
• Experience analyzing 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 analyzing 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