Manager - AI Strategy & Operations - MUSCP

Medical University of South Carolina; Charleston (SC); Hybrid; USD 90,000 - 130,000; Full time

Job summary

The Medical University of South Carolina is seeking a Manager of AI Strategy & Operations to oversee a multidisciplinary team responsible for the lifecycle of AI solutions. This role involves identifying opportunities for AI-driven efficiency, leading a team of data scientists, and quantifying ROI from AI implementations. Candidates should have a Master’s degree, 3–5 years of relevant experience, and strong leadership skills. The position is located in Charleston, South Carolina.

Qualifications

• Master’s degree required; PhD preferred.
• 3–5 years of relevant experience with leadership exposure in data science or AI.
• Ability to supervise teams and manage projects.

Responsibilities

• Oversee the lifecycle of MUSC’s AI solutions.
• Lead a team of Jr. Data Scientists and ML Engineers.
• Document and quantify financial and operational ROI from AI implementations.

Skills

Leadership

Collaboration

Operational improvement

Data Science

AI/ML familiarity

Education

Master’s degree

PhD preferred

Job description

Job Description Summary

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.

Primary Areas of Responsibility (with % Allocation)

1. AI Opportunity Discovery & Operational Strategy – 35%

• 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, AI Fine‑Tuning, Bias testing, Audit, etc.
• Identify existing AI Solutions primed for enhancement, build a pipeline visible to senior officers based on impact index to enterprise.

2. Team Leadership & Workforce Development – 25%

• 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.

3. Solution Development & Deployment Support – 20%

• 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.

4. ROI Measurement & Executive Reporting – 10%

• 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.

5. Partner Engagement & Thought Leadership – 10%

• 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.

Required Qualifications

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

Equal Opportunity Employment

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.

E‑Verify

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