Lead Data Scientist (Growth & Experimentation)

Join Fullscript as a Lead Data Scientist, where you'll be the analytics owner for one of our fastest-growing segments. This unique role combines the scope of a head of analytics with the autonomy of a senior individual contributor. You'll partner directly with key leaders across the organization to drive performance through data analysis and experimentation. As a foundational hire, you'll have the opportunity to shape the analytics function in this segment and grow the team over time.

• Lead the analytics efforts for one of Fullscript's fastest-growing segments, partnering with key stakeholders to drive business decisions.
• Own the experimentation engine, designing, running, and analyzing growth experiments to inform strategic investments.
• Build and maintain the reporting backbone, evolving an AI-augmented reporting stack to make performance easy to understand for executives.
• Customer obsession: you instinctively ground analysis in how real practitioners and patients use the product, and treat understanding their behavior as the source of good decisions
• Strong business judgment: you understand how growth, product usage, and operational drivers connect to revenue and contribution margin
• Experience in marketplace, eCommerce, SaaS, or healthcare businesses at scale
• Executive-grade communication: you can walk a GM through why a metric moved and what to do about it, in plain language
• 6+ years in data science, growth analytics, or quantitative business roles, with real depth in experimentation and causal inference — you've designed and shipped tests that changed business decisions
• Strong SQL and Python, and comfort working directly in large, imperfect datasets without a support team
• A track record of operating autonomously: scoping ambiguous questions, prioritizing your own roadmap, and driving work to a decision without close management
• Experience partnering with FP&A or strategic finance teams
• Experience building metric trees or driver-based performance frameworks
• Hands-on use of AI tools (LLMs, agents) in your analytics workflow
• Exposure to BI tools such as Sigma, Looker, Tableau, or Power BI
• Experience mentoring or managing analysts