Staff Data Scientist - Growth & Expansion

Accountabilities

• • Own the customer-growth outcome end to end, covering onboarding, activation, trial-to-paid conversion, multi-product adoption, retention, and expansion revenue.

  • Establish clear, trusted metrics for each stage of the customer lifecycle and ensure Growth, GTM, Finance, and Product teams work from a consistent evidence base.

  • Identify early- and mid-lifecycle behaviors that predict long-term expansion, including second-product adoption, higher-tier plans, and add-on attachment.

  • Translate behavioral and revenue data into segment-level insights that shape product priorities, growth initiatives, marketing investment, and go-to-market decisions.

  • Model the B2B2C customer journey, including agency signup, sub-account activation, adoption, and expansion, to identify where customer value compounds or is lost.

  • Partner with experimentation and causal-inference specialists to design and evaluate growth experiments rigorously, distinguishing causal effects from correlation.

  • Collaborate with Product Strategy, Growth, and other teams on trial-to-paid conversion, churn, and add-on initiatives to establish shared definitions and analytical models.

  • Set the technical direction for company-wide customer-growth measurement, including canonical metrics, segment definitions, and customer-value models using governed and certified data.

  • Develop reusable frameworks and methodologies for growth measurement and causal inference that Analytics Engineering and adjacent Data Science teams can adopt.

  • Serve as a trusted analytical advisor to Growth, GTM, Finance, and Product leaders, translating complex analysis into clear, decision-ready recommendations.

  • Influence roadmaps, investment decisions, and growth strategies through rigorous analysis without directly owning those functions.

  • Establish analytical standards for adjacent Data Science and Analytics teams, raising the quality and consistency of growth measurement across the organization.

  • Identify data gaps and collaborate with Analytics Engineering to improve the event taxonomy and data foundation required for funnel and customer-value analysis.

  • Use AI-assisted tools to accelerate exploration, documentation, analysis, and other analytical workflows.

  • Help establish reusable patterns and scalable foundations that can support the customer-growth mandate as the organization grows.

  Requirements

  • 9+ years of experience in product or growth analytics, data science, applied statistics, or a closely related discipline, with substantial experience across activation, retention, conversion, and expansion.

  • Demonstrated experience building a metric, measurement, or customer-value framework that has been adopted by multiple teams and used to drive measurable business outcomes.

  • Strong applied statistics expertise, including the ability to frame analyses around causal questions and recognize common limitations and failure modes of correlational analysis.

  • Practical experience partnering on experiments, including A/B test design, statistical power, guardrails, and rigorous interpretation of results.

  • Strong SQL skills and working proficiency in Python.

  • Experience working in a modern data environment involving Snowflake, dbt, or comparable technologies.

  • Proven ability to turn behavioral, product, and revenue data into segment-level insights that influence product, growth, or go-to-market decisions.

  • Comfortable working with imperfect or evolving data environments, using governed sources while helping identify opportunities to strengthen the underlying foundation.

  • Strong cross-functional influence and communication skills, with the ability to align Growth, GTM, Finance, Product, and Data teams around shared metrics and conclusions without direct authority.

  • Ability to communicate sophisticated analytical findings clearly to both technical and executive audiences.

  • Highly strategic, intellectually curious, pragmatic, and comfortable operating with broad ownership and ambiguity.

  • Experience with B2B SaaS, CRM, or product-led growth models is a plus, particularly freemium, trial, land-and-expand, or similar motions.

  • Exposure to usage-based, consumption-based, or add-on revenue models is advantageous.

  • Familiarity with Statsig or a comparable experimentation platform is a plus.

  • Experience with AI-assisted analytics workflows and/or mentoring analysts is desirable.

  Benefits

  • Annual salary range of $163,400–$220,000, depending on experience and role-related qualifications.

  • Fully remote work environment within the United States.

  • Staff-level scope with significant ownership of a company-wide customer-growth analytics mandate.

  • Opportunity to work cross-functionally with Growth, GTM, Finance, Product, Analytics Engineering, and Data Science teams.

  • High degree of autonomy and influence over analytical standards, measurement frameworks, and growth strategy.

  • Opportunity to advise senior leaders and directly influence product roadmaps, investment decisions, and go-to-market priorities.

  • Opportunity to develop reusable analytical and causal-inference frameworks that can scale across teams.

  • Potential to grow a dedicated analytics pod as the customer-growth mandate expands.

  • Exposure to a large-scale data environment supporting millions of businesses, substantial product usage, and complex customer journeys.

  • Opportunity to leverage AI-assisted tools and modern data practices to accelerate analytical work and decision-making.

  • Equal opportunity employment environment with voluntary demographic information collected separately for applicable compliance and reporting purposes.