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HighLevel is a SaaS company that develops an all-in-one marketing and sales platform for businesses and marketers. Its software brings together lead capture, appointment scheduling, pipeline management, websites, funnels, landing pages, and automated follow-up through phone, SMS, email, and social channels. HighLevel also provides API integrations, membership and course-management tools, and white-label options that let businesses offer the platform under their own brand. For job seekers, the company’s profile reflects work centered on building and supporting a broad business-automation product used across consulting, logistics, and other service-oriented organizations.
Staff Data Scientist, Revenue Retention — Remote in the United States
Lead causal analytics for core revenue retention and add-on monetization at HighLevel. Partner with CPaaS, Customer Success, Finance, and product teams to guide retention and growth decisions.
Description
- Lead causal analysis of core revenue retention and add-on monetization across CPaaS, AI add-ons, and other revenue streams
- Measure add-on revenue potential and identify the factors driving attachment and usage
- Use matching, difference-in-differences, survival and hazard models, synthetic controls, and related causal methods
- Work with Finance and RevOps to establish authoritative definitions and forecasting inputs
- Collaborate with Product Strategy, Growth, and Experimentation leaders on churn priorities and retention tests
- Provide analytical guidance to Customer Success, Finance, and Communications/CPaaS leadership
- Define analytical practices for Data Science and related analyst teams
- Direct company-wide revenue-retention measurement and maintain canonical GRR, NRR, churn, and add-on metrics
- Develop the retention analytics taxonomy in partnership with Analytics Engineering
- Create reusable frameworks for retention analysis and causal inference
- Use AI tools such as Claude for research, documentation, and analytical work
- Report through Product Analytics and Data Science while owning retention outcomes across teams
Requirements
- At least 9 years of experience in revenue or retention analytics, data science, or applied statistics, including substantial work with churn, retention, and monetization
- Applied causal-inference experience and the judgment to distinguish causal findings from artifacts of the data-generating process
- Experience reconciling complex financial, billing, and usage data and defining metrics trusted by Finance and product teams
- Advanced SQL skills and practical proficiency in Python
- Experience working with Snowflake and dbt
- Demonstrated impact from retention or monetization analysis on product, pricing, Customer Success, or lifecycle decisions
- Ability to work effectively with incomplete, evolving data and governed data sources
- Ability to influence product, Customer Success, Finance, and executive stakeholders without formal authority
- Experience with CPaaS or usage-based and consumption revenue models
- Background in B2B SaaS or CRM, including MRR or subscription billing, dunning, and involuntary-churn recovery
- Familiarity with Statsig or a similar experimentation platform
- Experience with AI-supported analytics processes
- Experience mentoring analysts
Benefits
- Remote-first working environment
- Equal Opportunity Employer
- Global organization built for remote work
- Opportunity to develop and lead a pod as the remit expands
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