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 puts key metrics to inform the company

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 — not just serving a single stakeholder

Data Scientist

Key skills