Lead Data Scientist - Healthcare
United States
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingLead 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.
From the employer’s posting
Key Responsibilities 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.
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.
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.
What you’ll bring
All qualificationsCore experience
- 8–10 years of experience in Data Science / Machine Learning roles.
- 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.
Preferred experience
- Experience with cloud platforms such as AWS, Azure, or GCP preferred.
Qualification wording
8–10 years of experience in Data Science / Machine Learning roles.
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.
Experience with cloud platforms such as AWS, Azure, or GCP preferred.
Tools in this posting
- Python
- SQL
- AWS
- Azure
- Google Cloud (GCP)
- Keras
- PyTorch
- TensorFlow
Source — Tool mentions in context
- 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.
- 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.
- 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.
Job description
Tiger Analytics is looking for experienced Data Scientists to join our fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.
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.
Key Responsibilities
- 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.
Requirements
- 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.
Benefits
This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
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Source & posting history
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
United States
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- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- May 11, 2026
- Recorded sightings
- 279
- Last seen by us
- Sep 26, 2026
- Employer says posted
- Apr 22, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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