Staff Data Scientist – Core Revenue Retention

This is a fully remote position, open to applicants in United States.

📋 Description

• Take ownership of the causal analysis related to core revenue retention and additional monetization across CPaaS, AI add-ons, and other revenue streams.

• Evaluate the revenue potential of add-ons and identify the factors influencing their adoption and usage.

• Utilize causal inference techniques such as matching, difference-in-differences, survival/hazard analysis, and synthetic control.

• Collaborate with Finance and RevOps to establish source-of-truth definitions and forecasting inputs.

• Work alongside Product Strategy & Growth on the TTP/churn initiative and with Experimentation leadership to assess retention strategies.

• Provide guidance to Customer Success, Finance, and Communications/CPaaS leaders.

• Establish analytical benchmarks for Data Science and related analyst teams.

• Define the technical framework for organization-wide revenue-retention measurement and take responsibility for canonical GRR, NRR, churn, and add-on metrics.

• Collaborate with Analytics Engineering to develop a comprehensive retention analytics taxonomy.

• Create reusable frameworks for retention and causal inference.

• Leverage AI tools such as Claude for exploration, documentation, and analysis.

• Report centrally to Product Analytics & Data Science while overseeing the revenue-retention results across departmental boundaries.

⛳️ Requirements

• Over 9 years of experience in revenue/retention analytics, data science, or applied statistics, with extensive knowledge in churn, retention, and monetization.

• Practical expertise in causal inference with a strong sense of when a result is genuinely causal versus a byproduct of data generation methods.

• Proficient in untangling complex financial, billing, and usage data and formulating metrics that can withstand scrutiny from Finance and product teams.

• Strong SQL skills and working proficiency in Python.

• Familiarity with a Snowflake and dbt environment.

• Proven track record of retention or monetization analyses influencing product, pricing, Customer Success, or lifecycle decisions.

• Ability to work effectively with incomplete, evolving data and utilize governed sources.

• Capacity to influence product, Customer Success, Finance, and leadership without direct authority.

• Experience with CPaaS or usage-based/consumption revenue models.

• Background in B2B SaaS or CRM; familiarity with MRR/subscription billing, dunning, and involuntary churn recovery.

• Knowledge of Statsig or a similar experimentation platform.

• Exposure to AI-assisted analytics workflows.

• Experience in mentoring analysts.

🏝️ Benefits

• Remote-first work environment.

• Equal Opportunity Employer.

• Global, remote-first organization.

• Opportunity to expand a pod as the mandate grows.