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Staff Data Scientist - Core Revenue Retention

GoHighLevel· Engineering – Data Platform
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Hybrid (India)Employee IndiaPosted 3w ago

About the role

Staff Data Scientist responsible for owning and driving revenue retention and add-on monetization across CPaaS, AI features, and related revenue surfaces. Cross-functional leadership across Product Analytics & Data Science, Customer Success, Communications/CPaaS, Finance, and Product Strategy to build a canonical retention framework, measurement standards, and persuasive analyses that influence product, pricing, lifecycle, and monetization decisions.

Responsibilities

  • Own the causal read on core revenue retention and add-on monetization across CPaaS, AI add-ons, and other revenue surfaces
  • Quantify add-on revenue opportunity across CPaaS and emerging AI features, and the drivers behind attach and consumption
  • Apply rigorous causal inference methods (matching, diff-in-diff, survival/hazard, synthetic control) to separate real signal from bias
  • Partner with Finance/RevOps on single-source-of-truth definitions and forecasting inputs; drive revenue-retention insights
  • Partner with Product Strategy & Growth and Experimentation leads on retention charter and rigorously test interventions
  • Advise Customer Success, Finance, and CPaaS leaders; set analytical standards adopted by DS and analysts
  • Set technical direction for company-wide revenue-retention measurement; define canonical metrics and data taxonomy
  • Build the retention and causal-inference framework with reusable methods for cross-team adoption
  • Use AI tooling to accelerate exploration, documentation, and analysis

Qualifications

  • 9+ years in revenue/retention analytics, data science, or applied statistics with deep experience in churn, retention, and monetization
  • Practical causal inference with judgment on causal vs artifacts of data
  • Experience untangling messy financial/billing/usage data and defining robust metrics
  • Strong SQL and Python; comfortable in a Snowflake + dbt environment
  • Track record of retention or monetization diagnoses influencing product/pricing/CS/lifecycle decisions
  • Ability to operate with imperfect, in-progress data and advocate for governed sources and improved pipelines
  • Cross-functional influence to align product, Customer Success, Finance, and leadership without formal authority

Skills

Required:Causal inferenceSQLPythonSnowflakedbtCross-functional influence

Benefits

  • Not specified in provided text
Last updated Oct 21, 2026. Interested? Apply on the company site.

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