资深数据科学家 - 增长与扩张
Staff Data Scientist - Growth & Expansion
关于HighLevel:
HighLevel是一个由人工智能驱动的业务操作系统,为代理商、企业家和中小型企业提供了构建、自动化和扩展的基础设施。目前,HighLevel支持全球150多个国家的中小企业,推动以真实客户成果为基础的社区驱动增长。
到目前为止,使用HighLevel运营的企业已产生超过70亿美元的生态系统价值,证明了规模化共享基础设施的影响。通过将对话、自动化和智能集中到一个系统中,我们帮助 businesses 更快地行动,减少复杂性并高效执行。
在平台背后,HighLevel每天处理超过40亿次API调用和25亿条消息事件。拥有250TB的分布式数据、250多个微服务和超过100万个域名支持,我们的架构专为性能、弹性和长期可扩展性而设计。
我们的团队
HighLevel在全球10多个国家拥有超过2000名团队成员,作为一个以远程办公为主、注重速度和所有权的全球性组织运作。我们重视主动性、清晰度和执行力,为有抱负的人创造空间,构建支持数百万企业的系统。在这里,创新蓬勃发展,想法受到庆祝,无论人们来自何处,人才始终是第一位的。
我们的影响
每个月,HighLevel为超过100万家企业提供超过15亿条消息、2亿个潜在客户和2000万次对话。这些数字背后是真实的人们在建立独立性、扩大机会和创造可衡量的影响。我们自豪地成为其中的一部分。
在我们的YouTube频道或博客文章中了解更多关于我们的情况。
职位描述:
我们正在招聘一名资深数据科学家,负责增长与扩展,全面负责塑造客户增长的每个团队的一个结果。在HighLevel,增长不是单一团队的专属:入职、激活、试用转付费、多产品采用和扩展是由增长部门、GTM、财务和产品团队共同推动的。你的工作是通过严格的细分层面理解,实际将新账户转化为不断增长的多产品客户——在一个B2B2C模型中,代理商注册后会激活子账户——这样公司就能投资于那些能持续增长的项目,而不仅仅是转化的项目。
这是一个广泛且跨职能的角色。你将与增长、GTM、财务以及任何推动客户增长的产品团队紧密合作;你将向产品分析团队中央汇报。
查看英文原文
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
EEO Statement:
The company is an Equal Opportunity Employer. As an employer subject to affirmative action regulations, we invite you to voluntarily provide the following demographic information. This information is used solely for compliance with government recordkeeping, reporting, and other legal requirements. Providing this information is voluntary and refusal to do so will not affect your application status. This data will be kept separate from your application and will not be used in the hiring decision.
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Originally posted on Himalayas