Responsibilities
- Design and maintain a scalable data model integrating product usage and telemetry data, customer success and support signals, and revenue data such as ARR, MRR, renewals, and pipeline
- Align and normalize data across systems, including Salesforce, product systems, and support tools
- Build clean, reusable datasets for analytics and BI
- Define and standardize core SaaS metrics, including Net Revenue Retention (NRR), Gross Revenue Retention (GRR), expansion, contraction, churn, renewal forecasting, and pipeline coverage
- Partner with Customer Success, Revenue Operations, Sales, and Finance teams to drive revenue insights
- Build models to forecast usage and revenue growth, predict expansion likelihood, and identify churn and saturation risk
- Apply statistical and analytical techniques such as time-series modeling, cohort analysis, regression, and probability modeling
- Design dashboards in Tableau that connect product usage to revenue outcomes, surface expansion-ready and at-risk accounts, and provide visibility into renewal pipeline and performance
- Ensure consistency through centralized metric definitions and SQL logic
Requirements
- 12+ years of experience in data modeling, reporting, and analysis, working closely with business partners
- Strong proficiency in Excel, SQL, Python, Tableau, or Power BI
- Strong data modeling skills in SQL are essential
- A proactive self-starter who thrives in ambiguous, high-speed environments while managing multiple priorities
- Skilled at communicating complex analytical findings to executive leadership and diverse stakeholders
- Experience with modern data warehouses such as Snowflake, BigQuery, or Redshift
- Deep understanding of SaaS metrics, including ARR, MRR, NRR, GRR, expansion, churn, and renewals
- Experience working cross-functionally with Customer Success, Revenue Operations or Sales, and Finance
- Prior experience designing semantic layers, data models, and KPI definitions for consistent reporting
- A Bachelor’s degree or equivalent in a quantitative field such as Business Analytics, Data Science, Computer Science, or Economics is required
Nice to Have
- MBA being highly desirable
