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Job Description Summary

The Chief Enterprise Insights Officer (CEIO) is a transformational executive responsible for advancing MUSC’s mission of becoming a fully data and AI-enabled enterprise. Evolving from the Chief Data Analytics Officer, the CEIO shifts MUSC from analytics delivery to enterprise-wide insights enablement, ensuring measurable impact across clinical care, research, education, and operations.

Entity

Medical University Hospital Authority (MUHA)

Worker Type

Employee

Worker Sub-Type​

Regular

Cost Center

CC002269 SYS - IS Senior Leaders

Pay Rate Type

Salary

Pay Grade

Health-00

Scheduled Weekly Hours

40

Work Shift

Job Description

The Chief Enterprise Insights Officer (CEIO) is a transformational executive responsible for advancing MUSC’s mission of becoming a fully data and AI-enabled enterprise. Evolving from the Chief Data Analytics Officer, the CEIO shifts MUSC from analytics delivery to enterprise-wide insights enablement, ensuring measurable impact across clinical care, research, education, and operations.

The CEIO stewards the Enterprise Data Foundry, builds next-generation capabilities in data engineering, AI/ML operations, and cloud platforms, and integrates solutions across federated data environments, research computing, educational technologies, and population health analytics. As chair of MUSC’s Data & AI Governance Council, the CEIO establishes policies for ethics, security, and compliance, while fostering a culture of data literacy, talent development, and evidence-based decision-making.

Serving as both an operator and public thought leader, the CEIO delivers financial and mission value (ROI/ROO), advances precision medicine and health equity, and positions MUSC as a statewide and national leader in digital health, research informatics, and trusted AI innovation.

Reporting & Scope:

• Reports to: Enterprise Chief Information Officer (CIO)

• Direct leadership: Leaders of Data Engineering, Analytics/BI, AI/ML Ops, Data Governance/MDM, Research Computing/HPC, and EdTech/Academic Analytics

• Decision rights (shared with Legal/Compliance/CISO as appropriate): Enterprise data & AI standards; model approval & monitoring; data-sharing agreements; platform selection; insights program budget & portfolio

• Work model: Hybrid, Charleston, SC (flexible within MUSC policy); Travel: up to ~20% across SC partners/affiliates

Key Responsibilities:

Strategic Leadership & Vision (20%)

• Define and champion MUSC’s enterprise insights vision, positioning data, AI, and automation as strategic enablers of the tripartite mission and statewide health leadership.

• Establish and evolve the Enterprise Data Foundry as MUSC’s trusted, scalable, and interoperable foundation for innovation.

• Develop a multi-year insights roadmap balancing foundational capabilities with transformational use cases (precision medicine, population health, digital education).

• Anticipate emerging technologies and industry trends and proactively incorporate them to maintain MUSC’s leadership position.

Mission Enablement Responsibilities (20%)

• Clinical Mission – Embed predictive and AI-driven insights into Epic and digital care models to advance population health, precision medicine, quality, and value-based care.

• Research Mission – Oversee HPC, research computing and compliance; enable translational science and clinical trials; foster statewide/national data consortia.

• Academic Mission – Advance learning analytics and adaptive EdTech; integrate insights into curricula, residency, and CME; align with academic governance.

• Operational Mission – Optimize workforce, finance, and operations; modernize platforms and M&A integration; expand automation and analytics to improve efficiency, patient experience, and ROI.

Technology & Platform Enablement (20%)

• Build and oversee Data Engineering, DataOps, and Cloud Operations teams, ensuring agility and reliability.

• Lead adoption of best-in-class platforms (Databricks-class analytics, Snowflake-class integration, Watsonx-class AI governance, Google HDE-class scale).

• Advance MDM transformation and enterprise data stewardship.

• Champion interoperability (FHIR APIs, HL7) to link Epic, academic, and research systems; enable federated learning and distributed models.

• Evaluate and integrate emerging technologies (generative AI, edge computing, synthetic data) to ensure future-readiness.

Governance, Security & Compliance (20%)

• Lead MUSC’s Data & AI Governance Council, setting policies for data quality, stewardship, and ethical use.

• Ensure compliance with HIPAA, ONC, NIH DMS, IRB, FDA, and state/federal regulations.

• Partner with the CISO and Compliance Officer to safeguard data privacy, cybersecurity, and AI safety.

• Define frameworks for ROI/ROO measurement and report to executive leadership and the President’s Council on risks, compliance, and outcomes.

Change Leadership & Partnerships (20%)

• Drive organizational change to a data- and AI-enabled culture, scaling training, upskilling, and adoption programs.

• Act as a bridge-builder across missions, partnering with leaders to align enterprise insights with institutional priorities.

• Cultivate statewide and national collaborations (HSSC, USC, Clemson, industry consortia), positioning MUSC as a trusted convener and thought leader.

• Secure philanthropy, grants, and partnerships to sustain and expand insights capabilities.

• Serve as a visible national voice for responsible AI, data ethics, and digital health innovation.

Additional Job Description

Requirements (Education, Skills, Experience, Licensure, Registry, Certification):

Education

Master’s degree in Health Informatics, Data Science, Computer Science, Business, or related field required.

Doctorate preferred; advanced certifications in AI, cloud, or cybersecurity highly valued.

Experience

12–15 years of progressive leadership in data, analytics, and digital transformation, ideally spanning healthcare and academic environments.

5–7 years of direct experience with AI/ML, advanced analytics, or automation initiatives, with proven ability to move innovations from pilot to enterprise adoption.

Demonstrated expertise in:

​​​-Research computing (HPC, GPU clusters, data-intensive science).

-Academic technology platforms (LMS, grants, digital learning, education

analytics).

-Multi-institutional collaborations (academic consortia, research

alliances).

-Master Data Management (MDM) transformation

-Building and leading Data Engineering, DataOps, and Cloud Operations

teams.

Proven success in:

-Value-based and population health analytics.

-Application rationalization, EHR optimization, and M&A technology

integration.

-Engaging Provosts, Deans, IRBs, and faculty governance bodies.

Skills & Competencies

-Visionary leadership with credibility across clinical, research, and academic domains.

-Expertise in data interoperability standards (FHIR, HL7, OMOP, CDISC, and academic federated identity standards like InCommon).

-Strong stakeholder engagement, governance, and change leadership.

-Ability to build high-performance, cross-functional teams that innovate at the intersection of healthcare, research, and education.

Success Measures

-Enterprise Data Foundry recognized as a statewide and national model, with successful MDM transformation creating a single source of truth.

-Broad adoption of insights and literacy programs, with measurable improvements in clinical outcomes, research productivity, and student success.

-Operational and financial value realized through platform rationalization, automation, and ROI/ROO tracking.

-Governance and compliance upheld, ensuring responsible AI, privacy, and regulatory alignment while advancing health equity and community impact.

-MUSC nationally recognized as a hub for enterprise insights and trusted AI, attracting grants, partnerships, and philanthropy.

Physical Requirements

• Mobility & Posture
  • Standing: Continuous
  • Sitting: Continuous
  • Walking: Continuous
  • Climbing stairs: Infrequent
  • Working indoors: Continuous
  • Working outdoors (temperature extremes): Infrequent
  • Working from elevated areas: Frequent
  • Working in confined/cramped spaces: Frequent
  • Kneeling: Infrequent
  • Bending at the waist: Continuous
  • Twisting at the waist: Frequent
  • Squatting: Frequent
• Manual Dexterity & Strength
  • Pinching operations: Frequent
  • Gross motor use (fingers/hands): Continuous
  • Firm grasping (fingers/hands): Continuous
  • Fine manipulation (fingers/hands): Continuous
  • Reaching overhead: Frequent
  • Reaching in all directions: Continuous
  • Repetitive motion (hands/wrists/elbows/shoulders): Continuous
  • Full use of both legs: Continuous
  • Balance & coordination (lower extremities): Frequent
• Lifting & Force Requirements
  • Lift/carry 50 lbs. unassisted: Infrequent
  • Lift/lower 50 lbs. from floor to 36”: Infrequent
  • Lift up to 25 lbs. overhead: Infrequent
  • Exert up to 50 lbs. of force: Frequent
    • Examples:
      • Transfer 100 lb. non-ambulatory patient = 50 lbs. force
      • Push 400 lb. patient in wheelchair on carpet = 20 lbs. force
      • Push patient stretcher one-handed = 25 lbs. force
• Vision & Sensory
  • Maintain corrected vision 20/40 (one or both eyes): Continuous
  • Recognize objects (near/far): Continuous
  • Color discrimination: Continuous
  • Depth perception: Continuous
  • Peripheral vision: Continuous
  • Hearing acuity (with correction): Continuous
  • Tactile sensory function: Continuous
  • Gross motor with fine motor coordination: Continuous
  • Selected Positions:
    • Olfactory (smell) function: Continuous
    • Respirator use qualification: Continuous
• Work Environment & Conditions
  • Effective stress management: Continuous
  • Rotating shifts: Frequent
  • Overtime as required: Frequent
  • Latex-safe environment: Continuous

If you like working with energetic enthusiastic individuals, you will enjoy your career with us!

The Medical University of South Carolina is an Equal Opportunity Employer. MUSC does not discriminate on the basis of race, color, religion or belief, age, sex, national origin, gender identity, sexual orientation, disability, protected veteran status, family or parental status, or any other status protected by state laws and/or federal regulations. All qualified applicants are encouraged to apply and will receive consideration for employment based upon applicable qualifications, merit and business need.

Medical University of South Carolina participates in the federal E-Verify program to confirm the identity and employment authorization of all newly hired employees. For further information about the E-Verify program, please click here: http://www.uscis.gov/e-verify/employees