Staff Data Scientist - Growth & Expansion

About HighLevel:

HighLevel is an AI-powered business operating system that gives agencies, entrepreneurs and SMBs the infrastructure to build, automate and scale. Today, HighLevel supports SMBs across 150+ countries, fueling community-driven growth rooted in real customer outcomes.

To date, businesses operating on HighLevel have generated over $7 billion in ecosystem value, demonstrating the impact of shared infrastructure at scale. By centralizing conversations, automation and intelligence into one system, we help businesses move faster, reduce complexity and execute efficiently.

Behind the platform, HighLevel powers more than 4 billion API hits and 2.5 billion message events daily. With 250 terabytes of distributed data, 250+ microservices and over 1 million domain names supported, our architecture is built for performance, resilience and long-term scalability.

Our People

With over 2,000 team members across 10+ countries, HighLevel operates as a global, remote-first organization built for speed and ownership. We value initiative, clarity and execution, creating space for ambitious people to build systems that support millions of businesses worldwide. Here, innovation thrives, ideas are celebrated and people come first, no matter where they call home.

Our Impact

Every month, HighLevel enables more than 1.5 billion messages, 200 million leads and 20 million conversations for the more than 1 million businesses we support. Behind those numbers are real people building independence, expanding opportunity and creating measurable impact. We’re proud to be a part of that.

Learn more about us on our YouTube Channel or Blog Posts.

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

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 Have:

• 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

Success in this role looks like:

• Growth, GTM, Finance, and product teams share one trusted value model connecting adoption to TTP, retention, and expansion - and invest behind it
• Expansion drivers (not just conversion drivers) are named, quantified by segment, and on the roadmap across the teams that own them
• Leaders across the growth motion make roadmap and spend calls off your analysis, not gut feel
• The customer-growth mandate has reusable patterns and the foundation to scale beyond one IC