Data Scientist Lead

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.

• 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.