Lead Data Scientist - Healthcare

Tiger Analytics, LLC; United States; On-site; USD 120,000 - 160,000; Full time

Job summary

Tiger Analytics, LLC is seeking an experienced Lead Data Scientist to drive advanced analytics initiatives. This role focuses on improving forecasting model accuracy and developing Generative AI solutions. Successful candidates will have 8–10 years of experience, strong expertise in forecasting models, and proficiency in Deep Learning frameworks such as TensorFlow or PyTorch. Knowledge of the healthcare domain is mandatory. This position offers a challenging and entrepreneurial environment for career growth.

Qualifications

• 8–10 years of experience in Data Science / Machine Learning roles.
• Strong hands-on expertise in forecasting models (time series, demand forecasting).
• Proven experience building Generative AI / Explainability models.

Responsibilities

• Lead the design and development of forecasting models.
• Build and deploy advanced Deep Learning models.
• Collaborate with stakeholders to translate business challenges into AI solutions.

Skills

Forecasting models

Python

Deep Learning frameworks

Generative AI / Explainability models

Stakeholder communication

Tools

TensorFlow

PyTorch

Keras

AWS

Azure

GCP

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.

• 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.

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.