Deputy CIO – Chief Enterprise Insights

Medical University of South Carolina•Charleston, SC

25d•Hybrid

About The Position

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. Evolving from the Chief Data Analytics Officer role, the CEI shifts MUSC from analytics delivery to enterprise-wide insights enablement. The CEI will steward the Enterprise Data Foundry, build next-generation capabilities in data engineering, AI/ML operations, and cloud platforms, and integrate solutions across federated data environments, research computing, educational technologies, and population health analytics. This leader will co-develop a business-led, system-level data governance framework and refine the current Data and AI Governance model to align with enterprise priorities. The CEI will establish policies for the security and compliance of MUSC’s data ecosystem while fostering a culture of data literacy, workforce development, and evidence-based decision-making.

Requirements

Master’s degree in health informatics, Data Science, Computer Science, Business, or related field required.
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.
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.

Nice To Haves

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

Responsibilities

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.
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.
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.
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.
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.