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FlyteHealth is transforming cardio-kidney-metabolic care through an integrated model combining behavioral lifestyle change, virtual clinical care, remote monitoring, and multidisciplinary care teams. They partner with employers, payers, PBMs, health systems, and other healthcare organizations to expand access, improve outcomes, and demonstrate measurable clinical and economic value.
You will build and scale FlyteHealth's Data & Analytics function as a hands-on leader reporting to the CEO. This role combines strategic leadership with technical execution, requiring close collaboration across Clinical, Product & Engineering, Finance & Revenue Cycle, Customer Success, Marketing, and external research and actuarial partners.
Key Responsibilities:
Data Strategy, Architecture & Governance: Define and execute company-wide data strategy and roadmap, aligning infrastructure and analytical priorities with clinical outcomes, client value, operational performance, and business growth. Own data architecture across ingestion, transformation, warehousing, and reporting, integrating EHR, CRM, communications, finance, claims, remote monitoring, and proprietary platform data. Establish longitudinal member data models, consistent identities, and standardized definitions. Ensure data reliability through quality testing, source reconciliation, lineage, freshness monitoring, documentation, and incident resolution. Establish governance, access controls, and approved data-use standards with Engineering, Security, and Compliance.
Analytics, Reporting & Decision Support: Own executive, board, operational, and client reporting, delivering consistent metrics and dashboards across clinical performance, member engagement, growth, revenue cycle, and unit economics. Analyze enrollment, activation, retention, marketing effectiveness, clinician capacity, utilization, and cost to serve. Partner with Clinical teams to define and evaluate health outcomes, including weight and metabolic measures. Build reusable data products, self-service analytics, and standardized reporting with documented data models and metric definitions.
Clinical Outcomes & Value Measurement: Lead medical and pharmacy claims analysis to evaluate healthcare utilization, medication costs, total cost of care, and program ROI. Establish defensible outcomes and economic measurement methods, including cohort selection, baselines, comparison groups, risk adjustment, and treatment of missing data and selection bias. Support internal and external research through validated datasets and reproducible analyses. Partner with Product & Engineering to prioritize forecasting, segmentation, predictive modeling, and AI/ML applications.
Team Leadership & Operational Excellence: Build and lead a high-performing team across data engineering, analytics engineering, analytics, and applied data science. Establish clear processes for intake, prioritization, stakeholder alignment, delivery commitments, and quality assurance. Own the data technology roadmap, vendor relationships, budget, and build-versus-buy decisions. Serve as a strategic data partner to the CEO and leadership team.
Success Metrics: Within 90 days, assess data architecture, sources, quality, reporting, and team capabilities; prioritize investments and align leadership on core metrics. Deliver dependable priority data pipelines and reporting with documented models and quality controls. Establish repeatable clinical, operational, financial, and client reporting with a credible outcomes measurement and ROI framework. Build a capable team, predictable delivery practices, reusable data assets, and self-service capabilities.
Requirements:
- 8+ years of progressive experience in data, analytics, data engineering, or applied data science, including 3+ years leading a team, function, or significant data transformation
- Demonstrated success building or scaling a data function in a startup, growth-stage digital health company, or similarly complex environment, combining strategic ownership with hands-on execution
- Strong proficiency in SQL and Python, with practical experience owning cloud data warehouses, data models, integration and transformation pipelines, orchestration, testing, and business intelligence tools
- Meaningful healthcare data experience spanning EHRs, clinical outcomes, medical or pharmacy claims, and financial or revenue-cycle data, including the ability to reconcile longitudinal records across imperfect source systems
- Strong statistical and analytical judgment, including cohort analysis, experimental or quasi-experimental methods, outcomes measurement, forecasting, and healthcare cost and ROI analysis
- Proven ability to recruit and develop technical talent, prioritize competing demands, manage vendors and budgets, and influence senior stakeholders through clear, commercially grounded recommendations
- Experience delivering secure, governed, well-documented data products and reporting for nontechnical users, with emphasis on quality, reproducibility, responsible data use, and measurable impact
Especially Valuable:
- Experience in virtual care, chronic-condition management, cardio-kidney-metabolic care, employer benefits, or value-based care
- Familiarity with AthenaOne, Salesforce, Vonage, Sage, or comparable systems, and modern data platforms such as dbt, Snowflake, Redshift, Looker, Tableau, or Domo
- Advanced training in statistics, health economics, actuarial science, data science, or related discipline
- Experience in real-world evidence, causal inference, healthcare interoperability, or production AI/ML
