Job Description

We are hiring a Senior Data Scientist in Woodland Hills, California with advanced expertise in AI agent architectures, LLMs, NLP, A2A Protocols, and Model Context Protocols (MCP). This role focuses on building interoperable, context-aware, and self-improving agents that transform clinical, administrative, and benefits platforms.

Role Overview of Senior Data Scientist

As a Senior Data Scientist, you will design and operationalize AI-driven multi-agent systems for healthcare. You will develop A2A protocols, build MCP pipelines, fine-tune LLMs, and deploy secure, compliant, and explainable AI solutions that address complex workflows such as benefit processing, clinical summarization, and patient engagement.

Key Responsibilities of Senior Data Scientist

Design and implement Agent-to-Agent (A2A) protocols enabling collaboration and negotiation between specialized AI agents.
Architect and operationalize MCP pipelines for memory-augmented LLM interactions across healthcare use cases.
Build multi-agent systems orchestrated by LLM-driven planning modules to support prior authorization, claims processing, and engagement.
Fine-tune domain-specific LLMs such as medical BERT or BioGPT for document understanding and personalized recommendations.
Develop retrieval-augmented generation (RAG) systems for knowledge grounding across structured (FHIR, ICD-10) and unstructured sources (EHR notes, chat logs).
Collaborate with engineers to build secure and explainable agent pipelines compliant with HIPAA, CMS, and NCQA.
Lead research in agent memory, RLHF, and context-aware planning.
Deploy models via robust MLOps pipelines with versioning, monitoring, and continuous improvement.

Required Qualifications

Master’s or Ph.D. in Computer Science, Machine Learning, or Computational Linguistics.
7+ years in applied AI with focus on LLMs, transformers, NLP, or agent systems.
Hands-on experience with A2A protocols, LangGraph, AutoGen, CrewAI, or similar orchestration tools.
Practical implementation of MCP for conversational memory and modular agent interactions.
Strong coding skills in Python and ML/NLP libraries like Hugging Face Transformers, PyTorch, LangChain, spaCy.
Familiarity with healthcare benefits, claims data, and eligibility systems.
Experience with FHIR, HL7, ICD/CPT, and X12 EDI.
Cloud-native experience in AWS, Azure, or GCP including Kubernetes and Docker.

Preferred Qualifications

Expertise in MCP + VectorDB integration for agent memory.
Prior deployments of LLM-based agent systems in healthcare.
Experience with voice AI or automated care navigation.
Published research or patents in agent architectures or contextual AI frameworks.

Additional Skills

MCPc
Core NLP
AI development
Azure cloud

Work Model

Location: Woodland Hills, CA
Engagement: Full-time
Work Mode: Onsite or Hybrid depending on business needs

Why Apply for the Senior Data Scientist Role?

Opportunity to design next-gen healthcare AI systems.
Work with cutting-edge LLMs and multi-agent architectures.
Collaborate with cross-functional teams on meaningful projects.
Lead research and innovation in contextual AI.
Competitive role in a highly impactful environment.

Ready to Apply?

If you are an innovative Senior Data Scientist passionate about AI agents, LLMs, and healthcare transformation, we encourage you to apply.

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FAQs – Senior Data Scientist

1. What is the main focus of this Senior Data Scientist role?
Developing AI agents, LLMs, NLP, A2A protocols, and MCP for healthcare workflows.

2. Where is the role located?
Woodland Hills, California.

3. How many years of experience are required?
At least 7 years in AI and NLP development.

4. Are healthcare data standards required?
Yes, knowledge of FHIR, HL7, ICD, and EDI formats is essential.

5. What protocols are relevant to this role?
A2A (Agent-to-Agent) protocols and Model Context Protocols (MCP).

6. Which languages and tools must I know?
Python, Hugging Face Transformers, PyTorch, LangChain, spaCy.

7. Is cloud experience required?
Yes, AWS, Azure, or GCP with Kubernetes and Docker.

8. Will I lead research?
Yes, including agent memory systems, RLHF, and contextual planning.

9. What LLMs are relevant?
Healthcare-specific models like BioGPT or medical BERT.

10. Will I design retrieval systems?
Yes, using RAG and VectorDB for dynamic knowledge grounding.

11. What compliance frameworks apply?
HIPAA, CMS, and NCQA.

12. Is this a leadership role?
Yes, you will guide research and collaborate with cross-functional teams.

13. Is publishing encouraged?
Yes, research and innovation are part of the role.

14. How is success measured?
By delivering secure, compliant, and scalable AI agent solutions.

15. How do I apply?
Apply online and explore more at Check out other positions.