Staff Data Scientist - Core Revenue Retention

📋 Description Own the causal read on core revenue retention and add-on monetization — gross and net revenue Quantify add-on revenue opportunity across CPaaS and emerging AI features, and the drivers behind Apply rigorous causal inference (matching, diff-in-diff, survival/hazard, synthetic control) where Partner with Finance/RevOps on single-source-of-truth definitions and forecasting inputs; drive the Partner with the Product Strategy & Growth org on the TTP/churn charter, and with the Act as a trusted analytical advisor to Customer Success, Finance, and Communications/CPaaS leaders 🎯 Requirements 9+ years in revenue/retention analytics, data science, or applied statistics, with deep experience Practical causal inference with sound judgment about when a result is causal vs. an artifact of how Comfort untangling messy financial/billing/usage data and defining metrics that survive scrutiny Strong SQL and working proficiency in Python; comfort in a Snowflake + dbt environment Track record where a retention or monetization diagnosis changed a product, pricing, CS, or Comfort amid imperfect, in-progress data — you consume governed sources and raise the bar rather 🎁 Benefits EEO Statement: Equal Opportunity Employer, voluntary demographic information for compliance