Manager - AI Strategy & Operations - MUSCP

Medical University of South Carolina•Beaverton, OR

2d•Onsite

About The Position

The Manager of AI Strategy & Operations oversees a multidisciplinary team responsible for the full lifecycle of MUSC’s AI solutions whether built internally or acquired externally. This includes ongoing maintenance, fine‑tuning, and version management; rigorous evaluation of new AI vendors within a zero‑trust sandbox environment; and the productionization of novel AI solutions produced by AI Incubation partners and selected by senior leadership for enterprise‑wide scaling. This leader ensures that AI initiatives generate measurable efficiency gains, alleviate operational bottlenecks, and deliver strong ROI. The Manager collaborates closely with clinical, operational, IS, and research stakeholders to identify high‑value opportunities, translate needs into actionable AI solutions, and drive successful adoption and integration across MUSC.

Requirements

Master’s degree required
3–5 years of relevant experience with leadership exposure in data science, AI, analytics, operational improvement, or technical program management.
Experience collaborating with data scientists, ML engineers, or technical teams
Familiarity with applied AI/ML preferred.
Demonstrated ability to supervise teams and manage cross‑functional projects.
Proven experience partnering with operational or clinical leaders to identify efficiency improvements or workflow enhancements.

Nice To Haves

PhD preferred.

Responsibilities

Identify operational workflows poised for AI‑driven efficiency gains or cost savings.
Lead discovery workshops and needs assessments with departments across MUSC.
Build opportunity maps, prioritize initiatives, and align with enterprise strategic goals.
Develop cadenced maintenance, and AI Fine-Tuning, Bias testing, Audit, etc.
Identify existing AI Solutions primed for enhancement, build a pipeline visible to senior officers base targeted workflows based on impact index to enterprise.
Lead a team of Jr. Data Scientists, ML Engineers, and a Jr. Architect.
Provide mentorship, performance management, and resource planning.
Develop skill‑building programs and promote a collaborative AI culture.
Oversee scaling of AI prototypes and solutions into enterprise environments
Guide production readiness planning and ensure operational requirements are met.
Ensure compliance with AI governance, quality standards, and risk controls.
Process document, and orient pre-assessment deployment evaluations for senior leadership review
Document and quantify financial and operational ROI from AI implementations measure as indirect or direct returns in revenue.
Track performance metrics and present outcomes to senior leadership at quarterly and annual cadence.
Advise departmental leaders on AI feasibility, adoption readiness, and workflow fit provide professional assessments to partners of build vs. buy.
Serve as an institutional subject matter expert for applied operational AI showcase examples of intentional design, and successful implementations to encourage further AI application.
Eliminate barriers and advocate for streamlined AI integration.