Staff Data Scientist - Growth & Expansion

We need to output HTML fragment with sections: About the role, Responsibilities, Requirements, maybe Benefits? There's no benefits listed. Pay is given: "$163,400 - $220,000 a year". So we need a Pay section. Schedule not mentioned, so omit. Benefits not mentioned, omit. Also we have "About HighLevel" and "Our People", "Our Impact" etc. Those are not required sections per instruction: we only include sections when posting has real, specific content for it. The "About the role" is a heading; we should use

for section headings. The content after "About the Role:" is the description. We'll put that in

maybe multiple paragraphs. We need to preserve all substantive info, not invent or summarize away detail. We'll need to keep the details. We need to remove boilerplate: EEO statement, AI tools note, etc. Also remove "Learn more about us on our YouTube Channel or Blog Posts." That's maybe navigation? It's not boilerplate but maybe considered promotional; but it's part of About HighLevel. The instruction: Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The YouTube/Blog line is not exactly boilerplate but maybe considered navigation? It's a link suggestion; but we can keep? It's not essential to role. Safer to remove it as it's not substantive for role. Also remove "About HighLevel:" heading? The page already shows job title; we shouldn't repeat job title as heading. But "About HighLevel:" is not a heading per instruction; it's just a label. We could treat it as a paragraph? The instruction: Use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So only those specific headings become

. Other headings like "About HighLevel:" should not be

. We could either drop it or keep as

with bold? But we must not invent headings. Probably we should just treat the content as prose under maybe no heading. But we need to preserve all substantive information. The "About HighLevel:" paragraph provides context about company; it's substantive. We'll keep it as a

(maybe preceded by a

? No, not allowed). So just a

. Similarly "Our People", "Our Impact" are also substantive but not required headings; we could keep them as paragraphs. However they might be considered boilerplate? They are about company culture; but they are substantive. The instruction says preserve ALL substantive information; do NOT invent or summarize away detail. So we should keep them. But we need to avoid duplication: there may be duplicated lines? Not seeing. We'll output:

About HighLevel: ...

Then

About the role

then the role description paragraphs. Then

Responsibilities

then

• ... each bullet. Then

  Requirements

  then
  • ... each bullet. Then maybe

    Nice to Have

    ? Not in allowed headings list; but we could treat as

    Nice to Have

    ? The instruction only lists certain headings; but we could still include if content exists. However they said "Use

    for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." The e.g. suggests those are examples, not exclusive. But they say "Prefer a few substantive sections over many thin ones." So we could include Nice to Have as a section if we want, but maybe better to incorporate into Requirements? But they are separate. I'd include a

    Nice to Have

    with list. Then

    Pay

    with the salary range. We must not include Schedule or Benefits. We must not include EEO statement etc. We'll need to strip out the "Success in this role looks like:" maybe that's part of responsibilities? It's after Requirements. Could be its own section but we could incorporate into Responsibilities or Requirements? It's more about outcomes. Could be its own section "Success in this role looks like:" but not in list. Might be better to incorporate into Responsibilities as a paragraph. However we need to preserve all detail; we can add a

    after Requirements describing success. But the instruction: Prefer a few substantive sections over many thin ones. So maybe we keep Responsibilities, Requirements, Nice to Have, Pay. And embed the success description within Responsibilities as a paragraph. Let's extract the role description text after "About the Role:" until "Responsibilities:". We'll copy that paragraph. Now responsibilities list: each bullet starts with a bold phrase? We'll just capture the sentences. Responsibilities list: - 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 Now Requirements list: - 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 list: - 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 Pay: "$163,400 - $220,000 a year" Now we need to output HTML fragment only. We'll wrap sections in

    and content. We'll need to escape any HTML special characters? Not needed. We'll produce:

    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.

    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