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# Lead Data Scientist - Healthcare

- **Company:** Tiger Analytics
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Clinical Data Repository, Cloud Computing, Computer Programming, Python (Programming Language), Machine Learning, Tensorflow, SQL Databases, Pytorch, Large Language Models, Deep Learning, Generative AI, Keras, Build Management, Scikit Learn
- **Published:** July 26, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=92f93197ca4d0f33

## About the Role

We are seeking an experienced Lead Data Scientist to drive advanced analytics initiatives focused on improving forecasting model accuracy and developing Generative AI solutions for explainability. This role requires a strong blend of machine learning expertise, forecasting experience, deep learning knowledge, and hands-on healthcare domain understanding., * 8-10 years of experience in Data Science / Machine Learning roles.

 * Strong hands-on expertise in Forecasting models (time series, demand forecasting, predictive analytics).
 * Experience with Deep Learning frameworks such as TensorFlow, PyTorch, or Keras.
 * Proven experience building Generative AI / Explainability models using LLMs, SHAP, LIME, or similar frameworks.
 * Mandatory experience working in the Healthcare domain.
 * Strong programming skills in Python, SQL, and ML libraries.
 * Experience with cloud platforms such as AWS, Azure, or GCP preferred.
 * Excellent stakeholder communication and leadership skills.

## Description

* Lead the design, development, and enhancement of forecasting models to improve prediction accuracy and business outcomes.
 * Build and deploy advanced Deep Learning models for large-scale structured and unstructured datasets.
 * Develop Generative AI / Explainable AI solutions to provide transparent and interpretable insights from predictive models.
 * Analyze healthcare datasets including claims, patient, provider, operational, or clinical data.
 * Collaborate with business stakeholders, product teams, and engineering teams to translate business challenges into scalable AI solutions.
 * Monitor model performance, retrain models, and optimize algorithms for production environments.
 * Mentor junior data scientists and provide technical leadership across the project.
 * Ensure compliance with healthcare data privacy and governance standards.


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