Manager - AI Strategy & Operations - MUSCP

MUSC Health; Charleston (SC); On-site; USD 90,000 - 120,000; Full time

Job summary

MUSC Health is seeking a Manager of AI Strategy & Operations to oversee a team responsible for the lifecycle of AI solutions. This role involves evaluating vendors, developing strategy, and ensuring operational effectiveness. The ideal candidate will have a Master's degree and 3–5 years of relevant experience in data science, AI, and operational improvement. Responsibilities include identifying AI opportunities, leading a team, and measuring ROI on AI implementations. 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, AI, or operational improvement.
• Experience collaborating with technical teams and familiarity with applied AI/ML preferred.

Responsibilities

• Oversee a multidisciplinary team responsible for AI lifecycle management.
• Identify operational workflows for AI-driven efficiency gains.
• Lead a team of Junior Data Scientists and ML Engineers.

Skills

Leadership

Data Science

Machine Learning

Operational Improvement

Technical Program Management

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, including ongoing maintenance, fine‑tuning, and version management. The role rigorously evaluates new AI vendors within a zero‑trust sandbox environment, productionizes novel AI solutions produced by AI Incubation partners, and 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)

• 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, and AI Fine‑Tuning, Bias testing, Audit, etc.
  • Identify existing AI solutions primed for enhancement, build a pipeline visible to senior officers and base targeted workflows on impact index to enterprise.
• 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.
• 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 documents, and orient pre‑assessment deployment evaluations for senior leadership review.
• ROI Measurement & Executive Reporting – 10%
  • Document and quantify financial and operational ROI from AI implementations, measuring indirect or direct returns in revenue.
  • Track performance metrics and present outcomes to senior leadership at quarterly and annual cadence.
• Partner Engagement & Thought Leadership – 10%
  • Advise departmental leaders on AI feasibility, adoption readiness, and workflow fit; provide professional assessments to partners on build versus 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.

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.

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