Data Analyst - Service and Operations Analytics

Data Analyst – Service & Operations Analytics

Salary range: $120,000 - $140,000 per year

About Vanna Health

Vanna is reimagining healthcare for people living with serious mental illness (SMI).

Today, our healthcare system is failing people with SMI. Despite $200B in annual medical spending, people with SMI die 20 years younger than their peers while suffering from higher rates of preventable disease (2x). They also face a higher risk of disfranchisement from society, including homelessness (6x), unemployment (30x), and incarceration (25x).

Our mission is to empower people with SMI to thrive by finding purpose and a sense of belonging in the community. The solution is social, not just medical. Vanna provides psychosocial rehabilitation and enables community-based care at scale, in close collaboration with existing healthcare and community organizations. Our model is designed to restore hope and nurture engagement by investing in a foundation of mutual trust and respect.

Vanna brings together an unprecedented team of proven entrepreneurs, individuals with

lived experience, and national leaders in behavioral health. We are committed to providing individuals with culturally inclusive support for all races, ethnicities, religions, sexual orientations, gender identities, and other social factors. With modern technology, extensive professional development opportunities, and a culture that actively promotes and fosters diversity, equity, inclusion, and belonging, we are redefining what it means to work in community health.

About the Role

Vanna Health is seeking a Data Analyst – Service & Operations Analytics to help clinical, operational, and business leaders understand how Vanna's services are performing and where opportunities exist to improve.

This role sits within Service Analytics organization and focuses primarily on Vanna's internal service and operational data, including data generated through Vanna’s proprietary platform, Vanna Connect. The analyst will use claims data and established analytical methods to independently generate key performance metrics and investigate program performance, identify meaningful variation, and translate findings into actionable insights for internal teams.

The successful candidate will be expected to analyze payer claims data to determine what is happening, where performance differs, what appears to be driving those differences, and what Operations should investigate or change.

What You Will Do

Service & Operational Analytics

• Analyze the member journey across attribution, outreach, engagement, assessment, service delivery, intervention, and follow-up.

• Monitor and investigate member engagement, assessment completion, timeliness, caseload, care-team activity, and service delivery.

• Compare performance across sites, markets, populations, programs, and operational teams.

• Identify trends, outliers, performance variation, and potential workflow bottlenecks.

• Conduct root-cause exploration using established analytical methods.

• Segment populations to understand where operational performance differs and identify factors associated with those differences.

• Translate findings into practical recommendations for Operations, Clinical, and other internal partners.

Reporting & Self-Service Analytics

• Own defined areas of recurring operational reporting.

• Develop Excel-based and other practical reporting solutions that provide teams with timely access to performance information.

• Use SQL and Databricks to independently query and analyze governed datasets.

• Help establish self-service access to frequently used operational data.

• Identify recurring analyses that should be standardized or automated.

• Partner with future BI/dashboard resources to transition high-value recurring reports into scalable reporting products.

Analytical Investigation

Within established metrics, definitions, and analytical standards, independently investigate questions such as:

• Why is assessment completion declining?

• Where are members dropping out of the service journey?

• Which sites or populations have lower engagement?

• How does caseload relate to service delivery?

• Where are workflow delays occurring?

• Which operational practices appear associated with better performance?

The analyst should be able to move from an identified operational problem through analysis, interpretation, and recommended follow-up without requiring a fully prescribed analytical approach.

Data Validation

• Validate data before using it for reporting or decision-making.

• Perform reconciliation and reasonableness checks.

• Identify missing, inconsistent, or unexpected data.

• Apply governed metric definitions and business rules consistently.

• Document analytical logic and assumptions.

• Escalate significant data-quality or methodological concerns to the appropriate Analytics lead.

• Partner with other Data team members and Data Engineering when underlying data issues affect analysis.

Business Partnership

• Develop strong relationships with Operations, Clinical, Product, and other internal teams.

• Translate operational questions into structured analyses using established analytical frameworks.

• Ask questions that clarify the underlying business problem rather than simply fulfilling report requests.

• Explain findings clearly to nontechnical stakeholders.

• Distinguish observed patterns from conclusions that require additional analysis.

• Recommend operational follow-up when supported by the data.

Required Qualifications

Required Skills & Experience

• 3–5 years of healthcare analytics experience, including hands-on experience working with medical and/or behavioral health claims data.

• Experience working with claims, eligibility, membership, provider, clinical, or operational data to support healthcare reporting and analysis.

• Experience performing data validation, reconciliation, reasonableness checks, and investigation of missing, inconsistent, or unexpected data.

• Strong data querying skills and demonstrated ability to independently query, join, validate, and analyze large healthcare datasets.

• Working knowledge of common healthcare claims concepts, including diagnosis and procedure codes, dates of service, place of service, provider information, paid/allowed amounts, utilization, and member eligibility.

• Experience analyzing operational or service-performance measures such as member engagement, outreach, assessments, service utilization, workflow completion, timeliness, caseloads, or program performance.

• Ability to apply established analytical definitions and methodologies consistently and recognize when a question requires more advanced methodological review.

• Ability to translate business questions into structured analyses and clearly explain findings to nontechnical operational and clinical stakeholders.

• Demonstrated ability to identify trends, variation, outliers, and potential drivers of performance rather than simply producing reports.

• Experience creating recurring reports, analytical outputs, or dashboards using Excel, BI tools, or similar reporting environments.

• Ability to work effectively in an evolving environment where data, workflows, and reporting requirements may not yet be fully standardized.

• Strong attention to analytical documentation, including metric definitions, assumptions, business rules, and limitations.

Preferred experience

• Medicaid, behavioral health, serious mental illness, population health, or care-management analytics.

• Experience with Databricks or another modern cloud data environment.

• Experience combining claims data with clinical, engagement, operational, or product data.