Staff Data Scientist - Growth & Expansion

HighLevel
$163,400 - $220,000Remote

About The Position

HighLevel is seeking a Staff Data Scientist, Growth & Expansion to own the customer growth outcome across all teams that influence it. This role is crucial for understanding and driving customer growth, from onboarding and activation to trial-to-paid conversion, multi-product adoption, and expansion revenue. You will work cross-functionally with Growth, Go-To-Market (GTM), Finance, and product teams, reporting to Product Analytics & Data Science. The position involves working with a developing data foundation, establishing rigorous measurement standards, and providing direction-setting analysis. This is a hands-on role where you will advise leaders, set growth measurement standards, and have the potential to grow a team as the mandate expands.

Requirements

  • 9+ years in product/growth analytics, data science, or applied statistics, with deep experience across activation, retention, conversion, and expansion motions
  • Track record where you built a metric or value framework that multiple teams drove real outcomes with - this role owns an outcome across boundaries, not reports for one team
  • Strong applied statistics - you design analysis to the causal question and know the failure modes of correlational reads
  • Fluency partnering on experiments (A/B design, power, guardrails) and interpreting results honestly
  • Strong SQL and working proficiency in Python; comfort in a Snowflake + dbt environment
  • Experience turning behavioral and revenue data into segment-level insight that changed a product, growth, or GTM decision
  • Comfort amid imperfect, in-progress data - you consume governed sources and raise the bar rather than rebuilding pipelines
  • Cross-functional influence - you align Growth, GTM, Finance, and product leaders on shared numbers without direct authority

Nice To Haves

  • B2B SaaS, CRM, or product-led growth background, especially freemium/trial and land-and-expand motions
  • Usage-based/consumption or add-on revenue exposure (expansion surfaces)
  • Familiarity with Statsig or a comparable experimentation platform
  • Exposure to AI-assisted analytics workflows; experience mentoring analysts

Responsibilities

  • Own the customer-growth outcome end to end - onboarding, activation, TTP, multi-product adoption, and expansion revenue - across Growth, GTM, and the product teams that drive it, with clear, trusted metrics at each stage
  • Identify which early and mid-lifecycle behaviors predict expansion (second product, higher plan, add-on attach), not just initial conversion, and turn it into a prioritized growth agenda
  • Connect product signal to GTM/marketing spend and Finance's growth targets - a single evidence base the whole growth motion shares
  • Model the B2B2C dynamic - agency → sub-account activation and expansion - and surface where compounding value is created or lost
  • Partner with the Experimentation & Causal Inference lead to design and read growth experiments rigorously; hold causal vs. correlational claims to a real bar
  • Partner with the Product Strategy & Growth org on the TTP/churn and add-ons charters so definitions and models are shared, not duplicated
  • Set the technical direction for how customer growth is measured company-wide - own the canonical metrics, segment definitions, and value model on governed, certified data that other teams build on
  • Build the growth-measurement and causal-inference framework - the standards and reusable methods that Analytics Engineering and adjacent DS teams reuse beyond this mandate
  • Translate findings into decision-grade guidance for Growth, GTM, Finance, and product leaders; influence roadmap and investment without owning them
  • Act as a trusted analytical advisor to Growth, GTM, and Finance leaders, and set the analytical standards that DS and analysts on adjacent teams adopt - raising the bar without direct authority
  • Flag data gaps to Analytics Engineering and shape the event taxonomy the funnel and value model depend on
  • Use AI tooling (Claude and similar) to move faster on exploration, documentation, and analysis

Benefits

  • AI-powered business operating system
  • Global, remote-first organization
  • Opportunity to build systems that support millions of businesses worldwide
  • Innovation thrives, ideas are celebrated and people come first
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