MUSC Health
Deputy CIO – Chief Enterprise Insights
MUSC Health, Charleston, South Carolina, United States, 29408
Job Description Summary
The Chief Enterprise Insights Officer (CEI) is a transformational executive responsible for partnering with enterprise leadership to advance MUSC’s transition into a fully data-enabled, insights-driven organization. The CEI will lead the development of a foundational data ecosystem with its embedded AI architecture that connects MUSC’s missions across clinical care, research, education, and operations, and will lead the development of MUSC’s Intelligent Data Platform, integrating an AI overlay.
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
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 core data architecture, data ecosystem health, and foster statewide/national data consortia.
Academic Mission – Advance learning analytics and integrate insights into academic governance and practice
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.
Co-evaluate and integrate emerging technologies (generative AI, edge computing, synthetic data) to ensure future-readiness.
Governance, Security & Compliance (20%)
Design the next MUSC’s Data & AI Technological Governance Framework, setting policies for data quality, data stewardship, and enabling 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 toward a more data- and AI-enabled decision-making enterprise.
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 in the data and analytics domain.
Secure philanthropy, grants, and partnerships to sustain and expand insights capabilities to drive continuous maturity of MUSC’s Data Ecosystem and emerging technology enablement.
Serve as a visible national voice for responsible AI, data ethics, and digital health innovation.
Requirements 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 is 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 are upheld, ensuring responsible AI, privacy, and regulatory alignment while advancing health equity and community impact.
MUSC is 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
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
#J-18808-Ljbffr
The Chief Enterprise Insights Officer (CEI) is a transformational executive responsible for partnering with enterprise leadership to advance MUSC’s transition into a fully data-enabled, insights-driven organization. The CEI will lead the development of a foundational data ecosystem with its embedded AI architecture that connects MUSC’s missions across clinical care, research, education, and operations, and will lead the development of MUSC’s Intelligent Data Platform, integrating an AI overlay.
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
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 core data architecture, data ecosystem health, and foster statewide/national data consortia.
Academic Mission – Advance learning analytics and integrate insights into academic governance and practice
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.
Co-evaluate and integrate emerging technologies (generative AI, edge computing, synthetic data) to ensure future-readiness.
Governance, Security & Compliance (20%)
Design the next MUSC’s Data & AI Technological Governance Framework, setting policies for data quality, data stewardship, and enabling 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 toward a more data- and AI-enabled decision-making enterprise.
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 in the data and analytics domain.
Secure philanthropy, grants, and partnerships to sustain and expand insights capabilities to drive continuous maturity of MUSC’s Data Ecosystem and emerging technology enablement.
Serve as a visible national voice for responsible AI, data ethics, and digital health innovation.
Requirements 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 is 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 are upheld, ensuring responsible AI, privacy, and regulatory alignment while advancing health equity and community impact.
MUSC is 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
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
#J-18808-Ljbffr