Staff Data Scientist - Growth & Expansion

About the Role:

We're hiring a Staff Data Scientist, Growth & Expansion to own one outcome - customer growth - across every team that shapes it. Growth at HighLevel isn't the property of a single team: onboarding, activation, trial-to-paid, multi-product adoption, and expansion are driven by the Growth org, GTM, Finance, and product teams across the company. Your job is to connect those efforts with a rigorous, segment-level understanding of what actually turns a new account into a growing, multi-product customer - in a B2B2C model where an agency signs up and then activates sub-accounts - so the company invests behind what compounds, not just what converts.

This is a broad, cross-functional role. You'll work closely with Growth, GTM, Finance, and any product team whose work drives customer growth; you report centrally to Product Analytics & Data Science for craft and standards and carry the growth outcome across organizational boundaries. You'll work amid a data foundation still being built, consuming governed and certified sources rather than rebuilding source logic, and raising the bar as you go. This is a hands-on, direction-setting Staff role - you advise Growth, GTM, and Finance leaders and set growth-measurement standards that analysts on adjacent teams adopt, with a path to grow a pod as the mandate scales.

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