Tiger Analytics
via Workable
Lead Data Scientist - Healthcare
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 7h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 146d ago
The date the source published, not the day we noticed it (2026-04-22). Last seen at its source 2h ago.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
United States
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $117.5k–130k/yr
Middle 50% of 713 listings that do state pay — Healthcare · all levels · United States · USD/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
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workable employer's own board first seen 10d ago · last seen 2h ago
The listing
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.