Senior Product Data Analyst, AI Health Cloud

BrightSpring Health Services

The Senior Product Data Analyst AI Health Cloud serves as the quantitative and interoperability backbone of the AI Health Cloud platform. You will define and operationalize product metrics experimentation frameworks and analytic outputs that drive product strategy and responsible AI execution.

You will also serve as the Interoperability SME bringing deep expertise in healthcare data exchange standards such as FHIR HL7 v2 C-CDA/CCD X12 and payerprovider integration patterns. You will work crossfunctionally across product engineering data science clinical and regulatory teams to ensure the platform delivers accurate analytics trusted AI and highquality data integration.

Product Strategy & Metrics

• Define the products North Star Metric and supporting metric framework.
• Translate product strategy into measurement plans and telemetry requirements.
• Conduct opportunity sizing scenario modeling and impact analyses that guide roadmap decisions.

Interoperability & Data Integration Leadership

• Serve as the Interoperability SME for the AI Health Cloud platform.
• Provide expert guidance on FHIR resources and profiles SMART on FHIR HL7 v2 interfaces CCDA/CCD X12 transactions and related healthcare integration workflows.
• Validate data quality mapping accuracy and schema alignment across multi-source healthcare data feeds (claims EMR/EHR registries clinical quality feeds).
• Partner with engineering and architecture to ensure interoperability pipelines support analytics AI and regulatory needs.
• Ensure integrations meet healthcare data and privacy regulations (HIPAA CMS NCQA).

Technical Analytics Leadership

• Collaborate with engineering and data science to design event schemas data contracts and telemetry instrumentation.
• Contribute analytic requirements to pipelines data models and semantic layers supporting the AI Health Cloud.
• Partner with ML Engineering to define and monitor model performance (drift accuracy calibration fairness hallucination rate latency cost-to-serve).

Requirements Experimentation & Delivery

• Translate stakeholder input into analytic specifications measurement plans and experiment designs.
• Lead A/B tests and causal analyses to evaluate feature and model impact.
• Support Agile delivery by ensuring telemetry readiness data quality and measurement alignment for every release.

Quality Compliance & Responsible AI

• Ensure analytics and data flows comply with regulatory and responsible AI standards.
• Build monitoring systems to detect drift data quality issues mapping errors and anomalous model behavior.
• Maintain audit-ready documentation for data lineage quality and AI governance.

Analytics Insights & Product Health

• Build dashboards and analyses to measure product health (usage latency reliability safety data quality).
• Conduct deep-dive analyses and root-cause investigations across product model and data domains.
• Deliver clear executive-ready insights and recommendations backed by analytic rigor.

Stakeholder Engagement

• Act as senior analytics and interoperability liaison for internal and external partners.
• Facilitate feedback loops to improve data quality model performance and workflow efficiency.
• Present findings KPIs and experiment outcomes to cross-functional leadership groups.

• 10 years in analytics data science interoperability product analytics or related healthcare data roles.
• Extensive experience with FHIR (R4 preferred) HL7 v2 C-CDA/CCD X12 and clinical/claims data integration.
• Expert-level proficiency with SQL and Python/R.
• Strong background in data modeling event instrumentation and semantic layer design.
• Deep understanding of key healthcare data sources (claims EMR/EHR quality programs registries).
• Experience in regulated healthcare environments with HIPAA CMS or NCQA.
• Exceptional communication and stakeholder leadership ability.

Preferred Qualifications

• Experience with cloud ecosystems (Azure GCP AWS) and interoperability frameworks (FHIR servers integration engines API gateways).
• Familiarity with MLOps and AI model monitoring tools.
• Proficiency with BI tools (Power BI Tableau Databricks AIBI).
• Experience supporting audit and compliance review processes.

Success Metrics

• Improved accuracy completeness and reliability of healthcare data integrations.
• Reduction in data quality issues mapping defects and interoperability failures.
• Strong telemetry coverage and model monitoring performance.
• Increased influence of insights on product strategy and OKRs.
• Audit-ready documentation and consistent measurement across the product lifecycle.

Why Join Us

• Lead analytics and interoperability strategy for a next-generation AI Health Cloud platform.
• Collaborate with industry-leading clinicians engineers data scientists and product leaders.
• Shape the future of responsible AI and healthcare data exchange at scale.
• Thrive in a flexible innovative mission-driven environment focused on meaningful impact.