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# Data Science Engineer

- **Company:** SATCON Inc
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon S3, Microsoft Azure, Health Informatics, Clinical Data Repository, Cloud Engineering, Continuous Integration, Data Auditing, DevOps, Github, Python (Programming Language), Machine Learning, Software Deployment, Large Language Models, Prompt Engineering, Model Validation, Generative AI, Backend, Fastapi, Scikit Learn, Xgboost, Machine Learning Operations, Api Design, Terraform, Docker
- **Published:** August 14, 2026
- **Apply:** https://www.dice.com/job-detail/36181772-7712-403d-bb76-5e6dadc2cbc5

## About the Role

* Experience: 2+ years of professional Data Science and Machine Learning experience.
 * Core Language: Expert-level proficiency in Python.
 * Generative AI: Hands-on experience with LLMs, Prompt Engineering, and RAG frameworks (LangChain, LlamaIndex, etc.).
 * Core ML: Strong command over Scikit-learn, XGBoost, and statistical reasoning.
 * API Development: Proven experience building backend services with FastAPI.
 * Cloud & DevOps: Direct experience with AWS (ECS, Lambda, S3), Docker, and infrastructure-as-code (Terraform).
 * CI/CD: Experience setting up pipelines in GitHub Actions or Azure DevOps.

Mandatory Healthcare Domain Experience:

 * Domain Knowledge: Must have direct project experience within Healthcare & Life Sciences.
 * Data Sources: Hands-on experience analyzing Real-World Data (RWD), Real-World Evidence (RWE), Claims, EHR/EMR, Clinical Data, and Patient Registries.
 * Solutions: Prior track record of building and deploying functional Healthcare Analytics or medical AI/ML solutions

## Description

We are seeking a highly skilled and independent Data Science Engineer to join our team for a high-impact contract opportunity. In this role, you will design, build, and deploy advanced AI/ML, NLP, and Generative AI solutions tailored for the Healthcare and Life Sciences domain. The ideal candidate brings a strong mix of statistical reasoning, advanced engineering (LLMs/MLOps), and deep experience handling complex clinical data, * AI/LLM Development: Design and implement Generative AI solutions using frameworks like LangChain, LlamaIndex, or CrewAI.

 * Model Engineering: Build, train, and evaluate traditional machine learning models (Scikit-learn, XGBoost) and advanced NLP pipelines.
 * Production Deployment: Develop robust, scalable ML APIs using FastAPI and deploy them into production environments.
 * MLOps & Infrastructure: Implement MLOps best practices using Docker, Terraform, GitHub Actions, and Azure DevOps for automated CI/CD pipelines.
 * Cloud Engineering: Manage and optimize data and model pipelines natively within AWS (ECS, Lambda, S3).
 * Data Evaluation: Apply rigorous model validation techniques and evaluation metrics to ensure safety, accuracy, and compliance.


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