Staff Data Scientist: Revenue Retention & Monetization

Highlevel; United States; Remote; USD 180,000 - 240,000; Full time

Job summary

HighLevel is seeking a Staff Data Scientist, Core Revenue Retention to own revenue-retention outcomes across CPaaS, add-ons, and customer success. You will build the retention model, ensure rigorous causal analysis, and set standards across teams, reporting to Product Analytics & Data Science.

This is a hands-on role that influences Finance, CS, and product decisions in a remote-first company. The role emphasizes cross-functional collaboration, advanced analytics, and scalable retention

Qualifications

• 9+ years in revenue/retention analytics or applied stats.
• Practical causal inference with judgment on causality vs artifacts.
• Untangling messy financial/usage data to define robust metrics.
• Strong SQL and Python; experience with Snowflake and dbt.
• Proven cross-functional influence on product, CS and Finance decisions.
• Comfort with governed data and improving data maturity.
• Ability to set retention analytics standards across teams.

Responsibilities

• Own the gross and net revenue retention and add-on monetization metrics across CPaaS and related surfaces.
• Quantify add-on revenue opportunities in CPaaS and AI features.
• Apply causal inference methods to uncover true signals.
• Partner with Finance/RevOps on definitions and forecasting inputs.
• Collaborate with Product Strategy and Growth on churn strategies and experiments.
• Advise CS, Finance, and CPaaS leaders and raise analytical standards.
• Set company-wide retention measurement direction and canonical metrics.
• Develop reusable retention analytics frameworks for scale.
• Leverage AI tooling to accelerate exploration and documentation.

Skills

Revenue retention analytics

Causal inference

Cross-functional influence

SQL

Python

Tools

Snowflake

dbt

Claude

Job description

HighLevel is seeking a Staff Data Scientist, Core Revenue Retention to own revenue-retention outcomes across CPaaS, add-ons, and customer success. You will build the retention model, ensure rigorous causal analysis, and set standards across teams, reporting to Product Analytics & Data Science.

This is a hands-on role that influences Finance, CS, and product decisions in a remote-first company. The role emphasizes cross-functional collaboration, advanced analytics, and scalable retention