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Flagler Health is building a clinical operating system for modern musculoskeletal care, partnering with MSK provider groups and specialty clinics to improve operations and patient outcomes. Following a Series B raise, the company is scaling its platform that bridges care delivery and clinic operations.
You will own product and operational analytics across the platform, responsible for understanding how the product and business are performing. This is not a research role but a strategic analytics position that directly influences executive decision-making. You will answer critical questions: where patients drop off in the journey, how patient cohorts behave over time, which clinical workflows are effective, and what hidden patterns in the data reveal new opportunities.
Working closely with Product, Engineering, and Operations, you will define and maintain core company metrics, ensuring consistent definitions across teams. You will partner with Product and Engineering to instrument new features correctly and measure their impact. Beyond recurring reports, you will tackle open-ended operational questions and investigate data anomalies to root cause. Your findings will be translated into clear recommendations for both technical and non-technical audiences, including leadership.
You will build and maintain dashboards, models, and data hygiene practices that enable repeatable analysis. Success requires strong analytical thinking paired with excellent communication skills—finding insights is half the job; getting the organization to act on them is the other half.
Required: 3+ years in data science or analytics, ideally product-driven environments. BS or equivalent with demonstrated strength in analytical reasoning. Proven depth in product/operational analytics (retention, cohort, funnel, engagement). Strong SQL and fluency in Python or R. Comfortable with ambiguous problems and defining analyses independently. Excellent communication and storytelling ability for mixed audiences. Thrives in fast-moving startups where priorities shift rapidly.
Nice to have: Healthcare or regulated data environment experience. Early-stage analytics infrastructure building experience.
