Data Scientist, Revenue Analytics
Core
Develop statistical models and measurement frameworks to quantify the impact of go-to-market investments on business outcomes across the customer lifecycle.
Role type
Senior IC data scientist (revenue analytics)
Builds
Statistical models, predictive models, and measurement frameworks for marketing, sales, and customer success initiatives
Domain
B2B SaaS / Revenue Analytics / Marketing Performance
Deliverable
production ML models | dashboards & analysis
Required skills
statistical inference, regression analysis, hypothesis testing, experimental design, predictive modeling, advanced SQL, Python or R, SaaS business metrics (ARR, CAC, LTV, retention, renewal, expansion)
Preferred skills
B2B SaaS experience, marketing effectiveness measurement (attribution, incrementality testing), causal inference techniques, cloud data platforms (Snowflake, Databricks, BigQuery, Redshift), BI tools (Tableau, Power BI, Looker)
Technologies
Python, R, SQL, Snowflake, Databricks, BigQuery, Redshift, Tableau, Power BI, Looker
Responsibilities
Develop statistical models to measure impact on pipeline, bookings, ARR, renewal, and expansion; Analyze paid media effectiveness (ROAS, CAC, ROI); Build predictive models for acquisition, conversion, retention, and churn; Design and evaluate experiments for incremental business impact; Partner with stakeholders to define success metrics; Develop forecasting models for revenue planning; Communicate findings to senior leaders via data visualization
Seniority
Senior, hands-on IC
