Job Description
Data Science & AI Manager - Healthcare
Location: 3 days a week Hybrid (Charlotte, NC)
Key Responsibilities
Agentic AI Strategy & System Orchestration
- Lead the strategy, architecture, and implementation of agentic AI systems for Healthcare Digital.
- Design and manage MCP servers that provide structured, secure tool access for AI agents across platforms including meal ordering, food production, and EVS task management.
- Build multi-agent systems with clear roles—e.g., planning agents, QA agents, data-retrieval agents, and operational copilots—that collaborate to support healthcare workflows.
- Develop governance and routing layers that enable AI agents to safely execute tasks, call tools, generate recommendations, and interact with structured operational data.
Product Intelligence & Embedded AI Agents
- Integrate agent-driven capabilities into Healthcare Digital’s platforms:
- Patient Meal Ordering: agentic nutrition checks, dietary rule enforcement, personalized recommendations.
- Food Production: prep-planning agents, demand forecasting agents, and waste-reduction optimization loops.
- EVS Task Management: task-ranking agents, routing agents, and real-time environmental monitoring copilots.
- Build AI copilots for associates and managers that support decision-making, reduce administrative load, and automate repetitive tasks.
- Ensure AI agents interact seamlessly with UI workflows, APIs, product logic, and underlying data systems.
Operational Data Science & Automation
- Build and deploy predictive models that feed agent decision-making, including:
- Meal demand forecasting
- EVS task prediction and prioritization
- Labor and staffing optimization
- Anomaly detection for operational issues
- Integrate model outputs with MCP-based agents to create closed-loop automation —agents that both detect and act, not just analyze.
- Translate findings into usable insights, dashboards, and operational recommendations for field teams.
Leadership & Cross-Functional Collaboration
- Coach and mentor a team of data scientists, ML engineers, and AI engineers focused on agent development and MCP integration.
- Partner with Healthcare Leadership (Culinary, EVS, Clinical Nutrition, Operations) to drive AI adoption and prioritize high-value opportunities.
- Collaborate with IT, and enterprise AI teams to align on architecture, security, and platform standards.
- Communicate complex AI and agent-based system concepts to non-technical stakeholders in clear, practical language.
Data, Governance & Responsible AI
- Ensure all AI and agent systems adhere to governance frameworks, including privacy, compliance, and HIPAA.
- Establish monitoring, auditability, and retraining workflows for both models and agents.
- Implement agent safety controls, including sandboxed tool access, role-based permissions, and fallbacks for critical tasks.
Qualifications
Required
- Bachelor’s degree in a relevant field or equivalent professional experience .
- 6+ years of experience in data science, AI engineering, or applied ML, including 2+ years of team leadership or technical management.
- Hands-on experience building agentic AI systems , including:
- Multi-agent workflows
- Tool-using agents
- Planning/monitoring agents
- Strong experience with MCP servers or similar agent integration frameworks (e.g., LangChain tools, AutoGen, OpenAI tool calling).
- Proficiency in Python, SQL, ML frameworks (PyTorch, TensorFlow, scikit-learn).
- Experience with cloud data and compute platforms (Azure, Databricks, AWS, or GCP).
- Strong understanding of LLMs, RAG pipelines, structured tool protocols, and knowledge graph integration.
- Excellent communication, stakeholder partnership, and product-oriented thinking.
Preferred
- Experience with healthcare, foodservice, hospitality, or operational environments.
- Familiarity with IoT data streams, workforce management systems, or real-time task operations.
- Background in optimization, reinforcement learning, or continuous planning agents.
Job Tags
3 days per week,