Staff Data Scientist – Core Revenue Retention

🕒 September 26

🇮🇳 India – Remote

⏰ Full Time

🔴 Lead

📊 Data Scientist

👻 Ghost score 15%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.Why this score:

• Open for 45 days.
• Jobs at this company usually fill in 64 days.
• No salary listed.

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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 across CPaaS and emerging AI features, and identify drivers behind attach and consumption • Apply causal inference methods including matching, diff-in-diff, survival/hazard, and synthetic control • Partner with Finance/RevOps on single-source-of-truth definitions and forecasting inputs • Partner with Product Strategy & Growth on the TTP/churn charter and with Experimentation to test retention interventions • Advise Customer Success, Finance, and Communications/CPaaS leaders • Set analytical standards for data science and analysts on adjacent teams • Set 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 Claude and similar AI tooling for exploration, documentation, and analysis

🎯 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 vs. an artifact of how the data was generated • Comfort untangling messy financial/billing/usage data and defining metrics that survive scrutiny from Finance and product alike • Strong SQL and working proficiency in Python • Comfort in a Snowflake + dbt environment • Track record where a retention or monetization diagnosis changed a product, pricing, CS, or lifecycle decision • Comfort amid imperfect, in-progress data — consuming governed sources and raising the bar rather than rebuilding pipelines • Cross-functional influence across product, Customer Success, Finance, and leadership without direct authority • CPaaS (telephony/messaging) 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

• Global, remote-first organization • Opportunity to work with a global team across 10+ countries • Path to grow a pod as the mandate scales

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