Principal Analytics Analyst - Healthcare Data

Surescripts serves the nation through simpler, trusted health intelligence sharing, in order to increase patient safety, lower costs and ensure quality care. The Principal Analytics Analyst - Healthcare Data leads high-impact, complex analytics initiatives that advance product strategy, commercial outcomes, and external credibility across the healthcare ecosystem.

Responsibilities:

• Lead the design and delivery of complex analytics initiatives (descriptive through prescriptive), selecting appropriate methodologies and ensuring statistical/analytical integrity
• Frame ambiguous, high-stakes questions into analytic strategies, measurement frameworks, and decision-ready insights that support product development and sales enablement
• Drive development of advanced models and decision frameworks (e.g., forecasting, propensity/risk models, segmentation, scenario analysis), including robust validation and monitoring recommendations
• Set expectations for analytic rigor: reproducibility standards, documentation norms, sensitivity analyses, and transparent communication of limitations and assumptions
• Influence the broader data/analytics ecosystem at Surescripts by defining reusable datasets, semantic layer requirements, KPI definitions, and analysis accelerators in collaboration with engineering and BI partners
• Mentor colleagues and team members; provide technical leadership through review, coaching, and development of best practices and playbooks
• Clearly communicate analytics methods and results to technical, executive, and client audiences, as needed
• Identify opportunities for new analytics capabilities, tools, or processes that increase impact, reliability, and speed-to-insight

Requirements:

• Master's degree in Data Science, Statistics, Epidemiology, Health Economics, or related field required
• 8+ years of experience in advanced analytics, with substantial healthcare analytics experience
• Evidence of leading complex, cross-functional analytics that drove material product, commercial, or strategic outcomes; preferred experience with medication adherence analytics, prior authorization and utilization management analytics, health economics and outcomes research (HEOR), and/or growth marketing analytics
• Expert-level SQL and strong Python/R; deep knowledge of statistical methods, machine learning (where appropriate), and analytical experimentation/measurement design
• Experience developing advanced analytical models and decision frameworks—including forecasting, risk or propensity modeling, segmentation, and scenario analysis—with demonstrated product or commercial impact and exposure to model validation and ongoing performance monitoring best practices
• Strong data visualization and executive storytelling skill; ability to build “narratives that travel” across stakeholder types
• Comfort working with large-scale healthcare datasets and navigating governance/privacy constraints responsibly
• Demonstrated ability to lead without authority: set direction, align stakeholders, and raise standards across teams
• Strong track record mentoring others and improving team capability through reusable assets and best practices
• PhD preferred but not mandatory