Staff Data Scientist – Growth & Expansion
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Job Description
Staff Data Scientist owning customer-growth measurement and expansion analytics at HighLevel, an AI-powered business operating system. Guiding Growth, GTM, Finance, and product investment through causal, segment-level insights.
Responsibilities:
- Own the customer-growth outcome end to end across onboarding, activation, trial-to-paid, multi-product adoption, and expansion revenue
- Identify early and mid-lifecycle behaviors that predict expansion and turn findings into a prioritized growth agenda
- Connect product signals to GTM/marketing spend and Finance growth targets
- Model the B2B2C dynamic of agency-to-sub-account activation and expansion
- Partner on the design and rigorous interpretation of growth experiments
- Establish shared definitions and models for trial-to-paid, churn, and add-ons
- Set technical direction for company-wide customer-growth measurement, canonical metrics, segment definitions, and value models
- Build reusable growth-measurement and causal-inference methods
- Translate findings into decision-grade guidance for Growth, GTM, Finance, and product leaders
- Act as a trusted analytical advisor and set standards adopted by adjacent data science and analytics teams
- Flag data gaps and shape the event taxonomy supporting the funnel and value model
- Use AI tooling such as Claude for exploration, documentation, and analysis
- Report centrally to Product Analytics & Data Science for craft and standards
- Help establish a foundation to scale the customer-growth mandate beyond one individual contributor
Requirements:
- 9+ years in product/growth analytics, data science, or applied statistics
- Deep experience across activation, retention, conversion, and expansion motions
- Track record of building a metric or value framework used by multiple teams to drive outcomes
- Strong applied statistics and ability to design analysis around causal questions
- Fluency partnering on experiments, including A/B design, power, guardrails, and result interpretation
- Strong SQL
- Working proficiency in Python
- Comfort in a Snowflake and dbt environment
- Experience turning behavioral and revenue data into segment-level insight that changed product, growth, or GTM decisions
- Comfort working with imperfect, in-progress data and governed sources
- Ability to influence Growth, GTM, Finance, and product leaders without direct authority
- B2B SaaS, CRM, or product-led growth background, especially freemium/trial and land-and-expand motions
- Usage-based/consumption or add-on revenue exposure
- Familiarity with Statsig or a comparable experimentation platform
- Exposure to AI-assisted analytics workflows
- Experience mentoring analysts
Benefits:
- Remote-first organization
- Equal Opportunity Employer
- Voluntary demographic information collection for compliance, with no effect on application status
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