About Us:
HighLevel is an AI powered, all-in-one white-label sales & marketing platform that empowers agencies, entrepreneurs, and businesses to elevate their digital presence and drive growth. We are proud to support a global and growing community of over 2 million businesses, comprised of agencies, consultants, and businesses of all sizes and industries. HighLevel empowers users with all the tools needed to capture, nurture, and close new leads into repeat customers. As of mid 2025, HighLevel processes over 4 billion API hits and handles more than 2.5 billion message events every day. Our platform manages over 470 terabytes of data distributed across five databases, operates with a network of over 250 microservices, and supports over 1 million hostnames.
Our People
With over 1,500 team members across 15+ countries, we operate in a global, remote-first environment. We are building more than software; we are building a global community rooted in creativity, collaboration, and impact. We take pride in cultivating a culture where innovation thrives, ideas are celebrated, and people come first, no matter where they call home.
Our Impact
As of mid 2025, our platform powers over 1.5 billion messages, helps generate over 200 million leads, and facilitates over 20 million conversations for the more than 2 million businesses we serve each month. Behind those numbers are real people growing their companies, connecting with customers, and making their mark - and we get to help make that happen.
Who You Are:
As a Data Scientist, you are a rare blend of analytical rigor and creative problem-solving. You possess deep expertise in predictive modeling, machine learning, and AI agent orchestration, with a strong foundation in SQL, Python, and modern frameworks. You are not only fluent in data and algorithms, but also in business context, translating complex insights into strategic actions that drive measurable outcomes.
You thrive in fast-paced, cross-functional environments where experimentation and iteration are valued. Whether it’s predicting churn, designing real-time scoring systems, or deploying AI agents using serverless infrastructure, you approach each challenge with curiosity, urgency, and precision. You are motivated by impact — building models that don’t just sit in notebooks, but get shipped into production and integrated into the operational fabric of Sales, Customer Success, and Product teams.
Your communication is as sharp as your code. You simplify the complex and shape narratives that help leadership, product managers, marketers, and frontline teams make better, faster decisions. You’re a strategic partner, not just a technical resource — equally comfortable debugging a model, writing a Slack alert, or designing an A/B test to validate an AI-driven intervention.
Above all, you’re excited about building the next generation of intelligent, agent-powered systems that not only understand the customer journey, but anticipate and improve it.
About the Role:
Predictive Churn Modeling & Customer Risk Scoring
Develop churn risk models using behavioral, transactional, and engagement signals across the customer journey.
Integrate features from product usage, CRM, support, billing, feedback channels and many more sources to create a comprehensive view of customer health.
Build and deploy real-time scoring systems that proactively flag accounts needing attention.
Design customer segmentation strategies to enable targeted retention campaigns and interventions.
AI-Powered Support for Retention
Leverage language models and agent frameworks to build intelligent assistants that support different teams in the business.
Deploy AI agents that summarize customer health, provide next-best actions, and auto-generate personalized outreach content.
Use retrieval and generation techniques to help teams access relevant insights, historical case references, and CS playbooks.
Experiment with prompt strategies and adaptive workflows to improve the performance of agent-based systems.
Insight Generation & Strategic Enablement
Conduct deep-dive analyses to understand drivers of retention and long-term customer value.
Enable leadership and GTM teams with dashboards, scorecards, and alerts derived from predictive insights.
Collaborate on testing strategies that validate the effectiveness of AI-driven touchpoints and communications.
Support the development of customer lifecycle metrics that reflect engagement, satisfaction, and risk.