Sr Data Scientist AI/ML (Only W2)

Location: Atlanta, GA Onsite Day 1 

Mandatory Areas
Must Have Skills

We are looking for Senior Data Scientist with 12+ Years

Skill 1 – 7+ Yers Exp - AI agent architectures, LLMs, NLP developing A2A Protocols and Model Context Protocols (MCP)
Skill 2 - 7+ Yers Exp - LLMs and NLP models (e.g., medical BERT, BioGPT)
SKill 3 - 7+ Yers Exp - retrieval-augmented generation (RAG)
Skill 4 – 7+ Yers Exp - coding experience in Python, with proficiency in ML/NLP libraries
Skill 6 - 7+ Yers Exp - AWS, Azure, or Google Cloud Platform including Kubernetes, Docker, and CI/CD


Key Responsibilities
• Build intelligent multi-agent systems orchestrated by LLM-driven planning modules to streamline benefit processing, prior authorization, clinical summarization, and member engagement.
• Fine-tune and integrate domain-specific LLMs and NLP models (e.g., medical BERT, BioGPT) for complex document understanding, intent classification, and personalized plan recommendations.
• Develop retrieval-augmented generation (RAG) systems and structured context libraries to enable dynamic knowledge grounding across structured (FHIR/ICD-10) and unstructured sources (EHR notes, chat logs).
• Collaborate with engineers and data architects to build scalable agentic pipelines that are secure, explainable, and compliant with healthcare regulations (HIPAA, CMS, NCQA).

Required Qualifications
• Master’s or Ph.D. in Computer Science, Machine Learning, Computational Linguistics, or a related field.
• 7+ years of experience in applied AI with a focus on LLMs, transformers, agent frameworks, or NLP in healthcare.
• Hands-on experience with Agent-to-Agent protocols, LangGraph, AutoGen, CrewAI, or similar multi-agent orchestration tools.
• Practical knowledge and implementation experience of Model Context Protocols (MCP) for long-lived conversational memory and modular agent interactions.
• Strong coding experience in Python, with proficiency in ML/NLP libraries like Hugging Face Transformers, PyTorch, LangChain, spaCy, etc.
• Familiarity with healthcare benefit systems, including plan structures, claims data, and eligibility rules.

Preferred Qualifications
• Deep understanding of MCP + VectorDB integration for dynamic agent memory and retrieval.
• Prior work on LLM-based agents in production systems or large-scale healthcare operations.
• Experience with voice AI, automated care navigation, or AI triage tools.
• Published research or patents in agent systems, LLM architectures, or contextual AI frameworks.