Staff Data Scientist - Core Revenue Retention at GoHighLevel
Job Description
📋 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
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