Data Scientist II responsible for modeling complex institutional problems and discovering insights for IEHP. Collaborating closely with stakeholders to provide enhanced data insight.
About the role
- Data Science & AI Manager leading agentic AI systems and team in Healthcare Digital to enhance patient experience. Prioritizing governance, automation, and cross-functional collaboration in AI developments.
Responsibilities
- 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.
- Integrate agent-driven capabilities into Healthcare Digital’s platforms: o Patient Meal Ordering: agentic nutrition checks, dietary rule enforcement, personalized recommendations. o Food Production: prep-planning agents, demand forecasting agents, and waste-reduction optimization loops. o 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.
- Build and deploy predictive models that feed agent decision-making, including: o Meal demand forecasting o EVS task prediction and prioritization o Labor and staffing optimization o 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.
- 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 Compass Digital, 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.
- Ensure all AI and agent systems adhere to Compass Group’s 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.
Requirements
- 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:
- o Multi-agent workflows
- o Tool-using agents
- o 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.
Benefits
- Equal opportunity employer
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Data Scientist I at IEHP responsible for maintaining and monitoring production models, discovering insights, and building algorithms. Focus on data science in the healthcare field from Rancho Cucamonga, California.
Data Science Advisor at Cigna - Evernorth leading the development of analytical solutions. Implementing machine learning and visualization to enhance decision - making for business objectives.
Senior Data Scientist leading innovative disease modeling approaches at healthcare AI company. Collaborating with teams to refine data - driven efforts in pharmaceutical commercialization.
Data Scientist developing disease modeling using statistical and machine learning techniques at a healthcare AI company. Collaborating with teams to ensure data - driven solutions and accuracy of models.
Data Science Manager leading a team to develop and deploy ML models for healthcare commercialization. Collaborating with cross - functional leaders to define product strategy at BranchLab.
Data Scientist developing and validating credit risk models at Enova. Collaborating with cross - functional teams to enhance lending criteria and verification procedures.
Data Scientist utilizing Machine Learning and statistics for business solutions at Suzano, a leader in sustainable products. Collaborating with teams and creating models for data - driven decisions.
Site Installation Software and Data Manager overseeing software deployment and data engineering in nuclear power project. Ensuring successful execution aligned with client and statutory requirements.
Data Scientist Intern addressing aviation industry challenges using machine learning and big data analytics at GE Aerospace. Collaborating with teams to develop insights from data for operational efficiency.