Chief Data & AI Officer (CDAO)

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This role ensures data is trusted, accessible, governed, and translated into actionable intelligence, while enabling scalable, responsible adoption of artificial intelligence.The CDAO plays a central role in supporting Michigan Medicine's evolution into a learning health system, orchestrating data and AI capabilities across clinical, operational, academic, and research domains. The role emphasizes platform enablement over centralization, fostering a distributed analytics and democratized AI model supported by strong governance, shared standards, and modern tooling.Organizational ScopeThe CDAO provides enterprise leadership across core domains including:Enterprise Data Strategy & GovernanceData Platforms, Architecture & EngineeringClinical & Operational Analytics (including Epic Cogito)Artificial Intelligence & Advanced Analytics (AI/ML/GenAI)Machine Learning Operations (MLOps) & AI Lifecycle ManagementData Literacy, Self-Service Analytics & AI EnablementData Infrastructure & Data Use EnablementAI Governance, Ethics & Responsible AIAI Orchestration, Automation, and Agentic MonitoringResponsibilities*Key ResponsibilitiesEnterprise Data & AI StrategyDefine and execute a comprehensive enterprise data and AI strategy aligned with Michigan Medicine's clinical, operational, academic, and research priorities.Position Michigan Medicine as a leader in AI-enabled healthcare delivery, academia, research, and operations.Serve as the executive advisor on data, analytics, and AI investments, opportunities, and risks.Data Governance, Strategy & Stewardship (Enterprise Ownership)Partnering across the enterprise, establish and lead enterprise data governance, including:Data ownership and stewardship modelsData policies, standards, and controlsData quality, integrity, and trust frameworksDefine and enforce data management standards, including:Metadata, cataloging, and lineageData classification and access controlsMaster and reference data strategiesEnsure all data assets are secure, compliant, governed, and usable at scale.Data Platforms, Architecture & InfrastructureLead enterprise data platform strategy and delivery, including:Data architecture and engineeringData pipelines, integration, and interoperabilityScalable data environments supporting clinical, administrative, academic, and research workloadsOversee clinical data infrastructure and architecture, enabling:Longitudinal patient recordsMaster Data ManagementInteroperability across systems and partnersSupport for advanced analytics and AILead and optimize the Epic Cogito environment, ensuring it is:Integrated into the broader enterprise data ecosystemPerforming, scalable, and aligned with reporting and analytics needsPartner with the CTO to ensure alignment between:Data platformsUnderlying infrastructure and cloud environmentsIntegration and interoperability platforms (API management, middleware)Analytics & Data Enablement (Distributed Model)Enable a distributed analytics model by:Providing shared platforms, tools, and governed accessSupporting domain-based analytics across clinical, operational, academic, and research teamsLead enterprise analytics capabilities, including:Clinical, operational, and financial analyticsRevenue cycle, administrative, and performance analyticsResearch and academic analyticsSelf-service BI tools and reporting environmentsPromote data democratization, ensuring users can:Access trusted dataBuild insights independentlyOperate within governance guardrailsArtificial Intelligence & Advanced AnalyticsLead enterprise AI strategy, including:Predictive analyticsMachine learning and deep learningGenerative AI and agent-based systemsIdentify, prioritize, and scale high-impact AI use cases across clinical, operational, and research domains.Partner with CHIO to enable clinical decision support and AI in care delivery.Partner with CAO to embed AI into applications and workflows.MLOps, AI Orchestration & Agentic MonitoringEstablish and lead Machine Learning Operations (MLOps) capabilities, including:Model development pipelinesDeployment, monitoring, and lifecycle managementModel versioning, retraining, and performance trackingImplement enterprise capabilities for:AI orchestration across systems and workflowsAgentic AI management and monitoringContinuous validation of model performance, drift, and biasEnsure AI is:Scalable and production-readyContinuously monitored and improvedIntegrated into enterprise workflowsAI Governance, Ethics & Responsible UseEstablish enterprise frameworks for AI governance and ethical use, including:Model transparency and explainabilityBias detection and mitigationAccountability and oversightPartner with legal, compliance, and clinical leadership to ensure:Responsible AI deploymentRegulatory alignmentPatient safety and trustData Literacy, AI Enablement & InnovationPromote a culture of data literacy and AI fluency across the organization.Establish enterprise capabilities for:Training, enablement, and adoptionSelf-service analytics and AI toolsInnovation sandboxes and experimentation environmentsEnable "vibe coding" and democratized AI experimentation in a controlled, governed environment.Cross-Functional Leadership & IntegrationPartner with: Application leaders - embed data and AI into applicationsTechnology leaders - align data and infrastructure platformsCustomer Experience - drive adoption of analytics and AI toolsHealth Informatics - align AI and analytics to clinical workflowsAcademics and Research - enable research data, advanced analytics, and AIEnterprise Delivery - integrate data/AI into portfolio prioritization and executionFinancial, Vendor & Workforce LeadershipLead investment planning and financial management for data and AI capabilities.Manage relationships with vendors and platform providers in data, analytics, and AI.Build and lead high-performing teams across: Data engineering and architectureAnalytics and BIAI/ML engineeringGovernance and enablementRequired Qualifications*Bachelor's degree in Data Science, Computer Science, Informatics, Engineering, or related field.15+ years of experience in data, analytics, and/or AI leadership roles.10+ years of leadership experience managing large, multidisciplinary teams.Demonstrated experience building and scaling enterprise data platforms and AI capabilities.Deep expertise in: Data architecture and engineeringAnalytics and BIAI/ML and modern data ecosystemsProven ability to operate in complex, federated, healthcare or academic environments.Desired Qualifications*Master's or PhD in Data Science, Informatics, Computer Science, Engineering, or related discipline.Experience in an academic medical center, health system, or research environment.Experience with Epic Cogito and healthcare data ecosystems.Track record of deploying AI at scale in research, academic, operational or clinical settings.Modes of WorkPositions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes.Additional InformationBenefits InformationWe offer a benefits package that includes comprehensive training and career development opportunities, generous retirement savings plans, ample paid time off, and a wealth of family care support: Background ScreeningMichigan Medicine conducts background screening and pre-employment drug testing on job candidates upon acceptance of a contingent job offer and may use a third party administrator to conduct background screenings. Background screenings are performed in compliance with the Fair Credit Report Act. Pre-employment drug testing applies to all selected candidates, including new or additional faculty and staff appointments, as well as transfers from other U-M campuses.U-M EEO StatementThe University of Michigan is an Equal Opportunity Employer. We are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants, including protected veterans and individuals with disabilities.Job Opening ID281965Working TitleChief Data & AI Officer (CDAO)Job TitleChief Data & AI Officer HlthWork LocationMichigan Medicine - Ann ArborAnn Arbor, MIModes of Work Hybrid Full/Part TimeFull-TimeRegular/TemporaryRegularFLSA StatusExemptOrganizational GroupExec Vp Med AffairsDepartmentMM HITS OCIO AdministrationPosting Begin/End Date8/24/2026 - 8/31/2026Career Interest Information Technology