Manager - AI Incubation Team - MUSCP

Primary Areas of Responsibility

• Evaluate AI ideas for enterprise value, feasibility, and alignment to MUSC priority areas.
• Build a multi-criteria prioritization process for incubation candidates.
• Serve as the key decision-maker for scoping and defining novel concepts.
• Manage a team of Jr. Data Scientists and ML Engineers.
• Ensure balanced allocation across multiple incubation projects.
• Foster an innovative, experimentation-friendly environment.
• Oversee feasibility testing, rapid prototyping, data assessment, and validation.
• Ensure prototypes are developed using responsible, ethical, and compliant AI practices.
• Document technical frameworks and readiness criteria for downstream teams.
• Career Development
• Coordinate with Strategy & Ops and Clinical Data teams to ensure smooth transition of validated prototypes.
• Prepare design packets, implementation recommendations, and risk notes for deployment teams.
• Maintain a pipeline of emerging AI opportunities across clinical, research, operational, and academic domains.
• Serve as the Center’s innovation engine to push the boundaries of applied healthcare AI.
• Seek to patent, and implement novel concepts into active execution and royalty streams for MUSC.

Key Annual Performance Objectives

• Deliver 2–3 validated AI innovations annually (deployed, validated, or patentable).
• Increase MUSC’s internal capacity for early-stage AI exploration.
• Reduce barriers preventing departments from pursuing high-impact AI ideas.

Required Qualifications

• Education: Master’s degree required; PhD preferred.
• Experience: 3–5 years of relevant experience with leadership exposure in AI, ML, data science, research engineering, or innovation environments.
• Technical Capability: Hands-on experience supporting AI projects, prototyping, data analysis, or early-stage concept development.
• Leadership: Demonstrated ability to lead technical contributors (data scientists, ML engineers).
• Innovation Skillset: Experience in rapid experimentation, feasibility analysis, or proof-of-concept development strongly preferred.