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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 — HighLevel, India Remote
Lead causal analysis of churn, retention, and add-on monetization for HighLevel’s AI-powered business operating system. Inform decisions across CPaaS, Customer Success, Finance, Product, and Growth.
Description
- Lead causal analysis of core revenue retention and add-on monetization across CPaaS, AI add-ons, and other revenue streams
- Assess add-on revenue potential across CPaaS and emerging AI features, identifying the factors that drive attachment and usage
- Use causal inference techniques such as matching, difference-in-differences, survival and hazard analysis, and synthetic control
- Collaborate with Finance and RevOps to establish authoritative metric definitions and forecasting inputs
- Work with Product Strategy and Growth on the TTP and churn charter, and with Experimentation to evaluate retention initiatives
- Provide analytical guidance to Customer Success, Finance, and Communications/CPaaS leadership
- Define analytical standards for data scientists and analysts on related teams
- Set the technical direction for company-wide retention measurement and own canonical GRR, NRR, churn, and add-on metrics
- Develop the retention analytics taxonomy with Analytics Engineering
- Create reusable frameworks for retention analysis and causal inference
- Use Claude and comparable AI tools for exploration, documentation, and analysis
Requirements
- At least 9 years of experience in revenue or retention analytics, data science, or applied statistics, including deep work on churn, retention, and monetization
- Hands-on causal inference experience and sound judgment in distinguishing causal findings from artifacts of the data-generation process
- Ability to interpret complex financial, billing, and usage data and define metrics that withstand Finance and Product scrutiny
- Strong SQL skills and working proficiency in Python
- Experience working in a Snowflake and dbt environment
- Demonstrated impact of retention or monetization analysis on product, pricing, Customer Success, or lifecycle decisions
- Ability to work with imperfect, evolving data, use governed sources, and improve analytical quality without rebuilding pipelines
- Ability to influence Product, Customer Success, Finance, and leadership without direct authority
- Experience with CPaaS, including telephony or messaging, or with usage-based and consumption revenue
- Background in B2B SaaS or CRM, including MRR, subscription billing, dunning, and involuntary-churn recovery
- Familiarity with Statsig or a comparable experimentation platform
- Experience with AI-assisted analytics workflows
- Experience mentoring analysts
Benefits
- Global, remote-first organization
- Collaboration with a global team spanning more than 10 countries
- Opportunity to grow a pod as the mandate expands
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