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# fulltime - Senior Data Scientist - Healthcare expert

- **Company:** E-Solutions
- **Location:** San Jose, CA, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Microsoft Azure, Cloud Computing, Continuous Integration, Graph Database, Python (Programming Language), Machine Learning, Neo4j, Tensorflow, Search Technologies, Data Ingestion, Pytorch, Large Language Models, Prompt Engineering, Deep Learning, Kubernetes, HuggingFace, Machine Learning Operations, Virtual Agents, Docker, Unsupervised Learning
- **Published:** September 25, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pmvzxqfk6z

## About the Role

IMP: - Skills - Agentic AI (A2A , MCP) , Azure Cloud , healthcare -payer space experience., PhD (preferred) or Master's in CS, AI, ML, Data Science, or related fields.

Strong hands on experience with:

 - Core ML & Stats (optimization, supervised/unsupervised learning)

 - NLP (semantic search, embeddings, text modeling)

 - MLOps (MLflow, Kubeflow, Airflow, Docker, CI/CD)

 - Proficiency in Python, PyTorch/TensorFlow, HuggingFace, LangChain, and cloud platforms.

 - Ability to translate complex ideas into scalable, real world systems.

 - Knowledge Graphs (RDF/OWL, Neo4j, graph ML)

 - LLMs & Transformers (fine tuning, RAG, prompt engineering)

Preferred

 - Healthcare insurance / Managed Care (MCO) experience - familiarity with claims, clinical workflows, risk models, or regulatory frameworks is a strong plus.

 - Experience with vector databases, hybrid semantic neural architectures, or agentic AI systems.

 - Background in explainable or responsible AI.

## Description

We're looking for a few Senior Data Scientist / AI Engineer with deep expertise in advanced Machine Learning, Large Language Models (LLMs) and Knowledge Graphs,.

This role is ideal for someone who enjoys solving complex problems, building intelligent systems end to end, and driving measurable impact in data rich environments.

What You'll Do:

 - Design advanced ML models across NLP, optimization, predictive modeling, and statistical learning.

 - Own end to end MLOps pipelines: data ingestion, training, deployment, monitoring, CI/CD.

 - Collaborate with engineering, product, and domain teams to deliver production ready AI solutions.


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