Maintain CenterWell data catalog, business glossary, KPI dictionary, lineage, and quality standards for cross-CenterWell assets
Partner with IT on unified data/platform strategy (UDAP) and guardrails for advanced self-service such as agentic, self-service analytics
Define standards and lifecycle for cross-CenterWell data products and feature stores; implement build-once approaches
Enable adoption through training, documentation, and support scaffolding
Develops and owns the cross-CenterWell interoperability strategy, enabling CenterWell businesses to access insights about their members both across the org, as well as external data from third party sources
Owns the interoperability integration strategy for standardly available data products for CenterWell stakeholders
Stand up intake, triage, and prioritization for cross-CenterWell data requests; reduce duplicative effort
Deliver common reporting and product/process monitoring; support pipelines for CenterWell-wide analytics
Jointly define, size, and prioritize predictive models and machine learning capabilities and backlog that maximizes value to CenterWell
Maintain deep technical expertise in advanced data science and AI (i.e., predictive modeling, NLP, classification) to upskill teams across Centerwell through new opportunities and approaches
Implement MLOps across CenterWell, in partnership with Enterprise teams, and responsible AI (privacy, fairness, explainability); partner with Legal, Compliance and Security
Partner with Enterprise teams to deliver enterprise-ready models, influence cross-enterprise platforms (ex – Florence), and integrate workflows to drive adoption and outcomes
Establish clear interfaces, RACI, and escalation protocol across CenterWell D&A Central, BUs, and Enterprise
Champion the elevation of data science capabilities across CenterWell, providing upskilling and reusable data assets that enables distributed teams to focus on faster insight generation and more sophisticated, novel analytics
Build a community of practice and coach leaders/ICs; attract and grow top D&A talent
Requirements
15+ years in Data and Analytics with demonstrated expertise in developing and deploying ML models in production environments
7+ years leading multi-disciplinary teams across complex enterprises
Proven success in cross-business engagement, data product development and strategy, shared services, and AI/ML
Healthcare experience with HIPAA/PHI; familiarity with HL7/FHIR; model risk management and interoperability strategies, infrastructure, and legal/compliance understanding
Hands-on with modern cloud data platforms and BI; strong communication and servant leadership
Ability to work Eastern Standard and Central Standard Time Zone
Tech Stack
Cloud
Benefits
medical, dental and vision benefits
401(k) retirement savings plan
time off (including paid time off, company and personal holidays, volunteer time off, paid parental and caregiver leave)