Staff Data Scientist – Core Revenue Retention

🔥 22 hours ago

🇺🇸 United States – Remote

💵 $163.4k - $220k / year

⏰ Full Time

🔴 Lead

📊 Data Scientist

👻 Ghost score 4%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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HighLevel

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2018

💼 Consulting

📦 Logistics

☁️ SaaS

💰 Series A on 2021-11

Consulting • Logistics • SaaS

HighLevel is an all-in-one marketing and sales platform designed to help businesses grow and succeed. The platform consolidates various marketing tools into a single solution, providing features such as lead capture through landing pages, surveys, forms, and calendars, as well as tools for nurturing leads via automated messaging across multiple channels including phone, SMS, email, and social media. HighLevel offers customizable solutions like online appointment scheduling, multi-channel follow-up campaigns, and pipeline management. Additionally, businesses can build websites, funnels, and landing pages using the intuitive page builder. HighLevel supports integrating with existing systems via API, and offers a membership platform for community building and course management. The platform is targeted towards marketers and offers white-labeling options for businesses to brand the software as their own. With a community-driven development approach and award-winning support, HighLevel is focused on empowering businesses to streamline their operations and enhance their marketing efficiencies.

📋 Description

• Own the causal read on core revenue retention and add-on monetization across CPaaS, AI add-ons, and other revenue surfaces • Quantify add-on revenue opportunity and the drivers behind attach and consumption • Apply causal inference methods including matching, difference-in-differences, survival/hazard analysis, and synthetic control • Partner with Finance and RevOps on source-of-truth definitions and forecasting inputs • Partner with Product Strategy & Growth on the TTP/churn charter and with Experimentation leadership to test retention interventions • Advise Customer Success, Finance, and Communications/CPaaS leaders • Set analytical standards for Data Science and adjacent analyst teams • Set the technical direction for company-wide revenue-retention measurement and own canonical GRR, NRR, churn, and add-on metrics • Shape the retention analytics taxonomy with Analytics Engineering • Build reusable retention and causal-inference frameworks • Use AI tooling such as Claude for exploration, documentation, and analysis • Report centrally to Product Analytics & Data Science while carrying the revenue-retention outcome across organizational boundaries

🎯 Requirements

• 9+ years in revenue/retention analytics, data science, or applied statistics, with deep experience on churn, retention, and monetization • Practical causal inference with sound judgment about when a result is causal versus an artifact of how the data was generated • Experience untangling messy financial, billing, and usage data and defining metrics that withstand scrutiny from Finance and product teams • Strong SQL and working proficiency in Python • Comfort in a Snowflake and dbt environment • Track record of retention or monetization diagnosis changing a product, pricing, Customer Success, or lifecycle decision • Comfort working amid imperfect, in-progress data and consuming governed sources • Ability to influence product, Customer Success, Finance, and leadership without direct authority • CPaaS or usage-based/consumption revenue experience • B2B SaaS or CRM background; experience with MRR/subscription billing, dunning, and involuntary-churn recovery • Familiarity with Statsig or a comparable experimentation platform • Exposure to AI-assisted analytics workflows • Experience mentoring analysts

🏖️ Benefits

• Remote-first work environment • Equal Opportunity Employer • Global, remote-first organization • Opportunity to grow a pod as the mandate scales