Senior Data Analyst – Payer & Claims Analytics

Vanna Health, Inc

3d • $145,000 - $165,000

About The Position

Vanna Health is seeking a Senior Data Analyst – Payer & Claims Analytics to help build the analytical capability supporting our growing relationships with leading health plans and our internal teams. This role will sit within Service Analytics and will be responsible for translating complex payer data—including medical and behavioral health claims, eligibility, attribution, and utilization data—into clear, defensible insights about member populations, program performance, outcomes, and value. This is not primarily a dashboard-production role. We are looking for an analyst who understands how health plans use data, knows the nuances of working with claims and eligibility data, and can independently investigate a business question from initial request through analytical interpretation. The ideal candidate has worked within or closely with a health plan and understands that getting the number is only the beginning: the analyst must be able to determine whether the number is correct, explain what is driving it, anticipate questions from sophisticated payer clients, and translate findings into actionable recommendations.

Requirements

• 6–8+ years of healthcare analytics experience, with substantial hands-on experience analyzing health plan, medical claims, behavioral health claims, eligibility, membership, attribution, utilization, and cost data.
• Deep knowledge of healthcare claims methodology, including continuous eligibility, member months, denominators, claims runout, reversals and adjustments, incurred versus paid considerations, utilization definitions, and cohort construction.
• Advanced data querying skills and demonstrated ability to independently analyze large, complex healthcare datasets.
• Proven experience designing analytical methodology, rather than solely applying predefined specifications, for ambiguous or complex payer questions.
• Experience defining populations, inclusion/exclusion criteria, baseline and measurement periods, comparison groups, utilization measures, PMPM metrics, and longitudinal analyses.
• Demonstrated ability to determine whether available data are sufficient to support a conclusion and to clearly articulate methodological limitations when they are not.
• Experience reconciling results across payer, claims, eligibility, operational, or clinical data sources and investigating material discrepancies.
• Strong understanding of healthcare utilization, cost, population health, and outcomes measurement.
• Experience evaluating associations between healthcare interventions, engagement, utilization, cost, and outcomes while appropriately distinguishing association from causal evidence.
• Ability to anticipate the methodological questions a sophisticated payer analytics team is likely to raise and prepare supporting analyses proactively.
• Strong written and verbal communication skills, including the ability to explain complex analytical methods, assumptions, limitations, and findings to executives and nontechnical audiences.
• Demonstrated ability to provide methodological guidance, peer review, or mentorship to other analysts.
• Ability to operate with substantial independence and exercise sound analytical judgment when findings have client, contractual, financial, or strategic implications.
• Comfort representing Analytics in senior leadership and client discussions when methodology, results, reconciliation, or interpretation are under review.

Nice To Haves

• Direct experience within a health plan, managed care organization, or payer analytics organization.
• Medicaid and/or behavioral health analytics experience.
• Experience with value-based care, total-cost-of-care, care-management, or population-health programs.
• Familiarity with HEDIS or other healthcare quality measures.
• Experience with Databricks or comparable cloud analytics platforms.
• Python or R experience.
• Experience presenting analytical methodology or findings directly to payer clients or senior healthcare executives.

Responsibilities

• Serve as a primary analytical partner for Vanna's payer relationships.
• Translate payer contractual, reporting, and business questions into clear analytical requirements and analyses.
• Analyze medical and behavioral health claims, eligibility, attribution, utilization, and other payer datasets.
• Develop and validate measures related to enrollment, engagement, utilization, quality, outcomes, and cost.
• Analyze ED, inpatient, outpatient, behavioral health, and other utilization patterns across populations and cohorts.
• Calculate and interpret measures such as member months, utilization rates, PMPM costs, and population-level trends.
• Account appropriately for claims runout, reversals, adjustments, eligibility periods, population changes, and other methodological considerations.
• Reconcile Vanna results with payer-reported results and investigate discrepancies.
• Anticipate questions clients are likely to ask and proactively identify analyses needed to answer them.
• Support recurring client reporting while progressively moving Vanna toward standardized, repeatable analytical products.
• Connect payer data with Vanna service data to understand the member journey from attribution and engagement through intervention, outcomes, utilization, and cost.
• Compare performance across populations, cohorts, markets, sites, and levels of engagement.
• Identify populations that are engaging—or failing to engage—with Vanna's services.
• Evaluate relationships between service delivery, member outcomes, and healthcare utilization.
• Partner with Service/Operations Analytics to investigate drivers of performance.
• Help develop the analytical foundation needed to evaluate Vanna's clinical and economic impact.
• Validate source data before using it for client or executive reporting.
• Identify anomalies, incomplete data, methodological limitations, and potential sources of bias.
• Clearly document analytical methodologies, assumptions, inclusion/exclusion criteria, and limitations.
• Partner closely with Vanna's Data Quality & Data Model Lead to establish consistent metric definitions and analytical standards.
• Work with Data Engineering to translate analytical requirements into reliable, reusable datasets in Databricks.
• Help reduce dependence on one-off analyses by identifying opportunities to standardize frequently used measures and datasets.
• Work directly with leaders across Operations, Clinical, Client Success, Finance, Product, and Data Engineering.
• Translate ambiguous business questions into structured analytical approaches.
• Present complex analyses in language that clinical, operational, payer, and executive audiences can understand.
• Distinguish between what the data demonstrates, what it suggests, and what cannot yet be concluded.
• Move beyond reporting what happened to explain why it happened, why it matters, and what Vanna should do next.

Benefits

• modern technology
• extensive professional development opportunities
• a culture that actively promotes and fosters diversity, equity, inclusion, and belonging

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed