Senior Data Scientist

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Scientist with a contract length in Woodland Hills, CA. The pay rate is unspecified. Key skills include 7+ years in applied AI/NLP in healthcare, strong Python proficiency, and experience with cloud-native development.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
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πŸ—“οΈ - Date discovered
September 17, 2025
πŸ•’ - Project duration
Unknown
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🏝️ - Location type
On-site
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πŸ“„ - Contract type
Unknown
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πŸ”’ - Security clearance
Unknown
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πŸ“ - Location detailed
Woodland, CA
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🧠 - Skills detailed
#FHIR (Fast Healthcare Interoperability Resources) #Docker #Langchain #ML (Machine Learning) #Cloud #Scala #Monitoring #"ETL (Extract #Transform #Load)" #Transformers #Azure #CMS (Content Management System) #SpaCy #PyTorch #Data Science #Libraries #Kubernetes #BERT #AI (Artificial Intelligence) #GCP (Google Cloud Platform) #Compliance #Hugging Face #Python #Deployment #AWS (Amazon Web Services) #NLP (Natural Language Processing)
Role description
Role: Senior Data scientist Contract Woodland hills CA(Onsite) JD: πŸ” What You’ll Do β€’ Design Agent-to-Agent (A2A) protocols for autonomous collaboration between AI agents (e.g., ClaimsAgent, EligibilityAgent). β€’ Build Model Context Protocol (MCP) pipelines for persistent memory and context-aware LLM interactions. β€’ Develop multi-agent orchestration systems for benefit processing, prior authorization, and clinical summarization. β€’ Fine-tune domain-specific LLMs (e.g., BioGPT, medical BERT) for document understanding and personalized recommendations. β€’ Implement RAG systems and structured context libraries using FHIR, ICD-10, EHR notes, and chat logs. β€’ Ensure compliance with HIPAA, CMS, NCQA while building scalable, explainable pipelines. β€’ Lead research in RLHF, memory-based agents, and context-aware planning. β€’ Contribute to MLOps pipelines for deployment, monitoring, and continuous improvement. βœ… What You Bring β€’ Master’s/Ph.D. in CS, ML, NLP, or related field. β€’ 7+ years in applied AI with LLMs, transformers, agent frameworks, or NLP in healthcare. β€’ Hands-on with LangGraph, AutoGen, CrewAI, and Model Context Protocols. β€’ Strong Python skills with Hugging Face, PyTorch, LangChain, spaCy, etc. β€’ Experience with healthcare data standards: FHIR, HL7, ICD/CPT, X12 EDI. β€’ Cloud-native development on AWS, Azure, or GCP with Docker/Kubernetes.