Staff Data Scientist - Core Revenue Retention
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Job Description
Structured overview of role & requirementsAbout This Role
Own core revenue retention and add-on monetization metrics across multiple teams including CPaaS, AI features, Customer Success, and Finance.
Build and maintain causal inference models to diagnose revenue churn and opportunities, setting company-wide measurement standards and reusable analytic frameworks.
Advise cross-functional leadership and coordinate analytics strategy to influence retention and monetization decisions without direct authority.
Minimum Requirements
9+ years experience in revenue/retention analytics, data science, or applied statistics focused on churn, retention, and monetization.
Strong SQL and Python skills; comfortable with Snowflake and dbt environments.
Experience working with complex financial, billing, and usage data to define credible metrics accepted by Finance and Product teams.
Work Experience Required: 9+ years in relevant analytics or data science roles.
Ideal Candidate Profile
Experienced in applying rigorous causal inference methods (e.g., diff-in-diff, survival analysis) in imperfect, evolving data environments.
Proven ability to influence cross-functional stakeholders (Product, Finance, Customer Success) through data-driven insights without direct reporting authority.
Familiarity with B2B SaaS subscription models, CPaaS or usage-based revenue, and AI-assisted analytics workflows is a plus but not mandatory.