Lead Data Scientist – Healthcare / GenAI / LLM

About the role

We are seeking a hands-on Lead Data Scientist with deep, recent healthcare data science experience and demonstrated production-level Generative AI (GenAI) and Large Language Model (LLM) expertise. This is a true data science and technical leadership role—not a BI, data engineering, operations research, or primarily traditional analytics position.

Responsibilities

• Own end-to-end development and deployment of sophisticated machine learning solutions, including model development, validation, deployment, monitoring, and productionization.
• Develop and deploy GenAI/LLM solutions in production (e.g., RAG, agentic AI, NLP/LLM applications, prompt or model evaluation).
• Work with clinical, patient, EHR/EMR, claims, population health, or other complex healthcare datasets, understanding regulatory challenges.
• Provide technical leadership: mentor and guide other data scientists, influence modeling and technical direction, partner with senior stakeholders, translate data science work into business or clinical outcomes.
• Manage multiple projects with competing priorities, lead cross‑functional teams, and deliver projects on schedule.

Requirements

• Bachelor’s degree or higher in a STEM field (Computer Science, Data Science, Statistics, Mathematics, Engineering, or related); Master’s in Data Science preferred.
• Minimum of seven (7) years of professional data science experience.
• Recent, substantive experience applying data science and machine learning within healthcare (hospital environment, medical informatics, healthcare IT, finance/revenue cycle, EHR/EMR data).
• Demonstrated hands‑on production experience with Generative AI and LLMs (RAG, agentic AI, NLP/LLM apps, prompt/model evaluation, etc.).
• Proven ability to lead data science teams, mentor junior staff, and drive technical direction.

Skills

• Advanced statistical analysis (regression, testing, probability/distributions).
• Machine learning methodologies (clustering, decision trees, neural networks, predictive modeling).
• Data science methodologies (time‑series forecasting, A/B testing, clustering, predictive analytics).
• Advanced SQL and database management.
• Programming and statistical analysis tools used in modern data science environments.
• Data modeling, algorithm development, data mining, visualization, pattern analysis.
• Business analytics, process analysis, workflow development, spreadsheets.
• Data architecture and design principles.
• Strong communication, data storytelling, ability to explain results to technical and non‑technical audiences.
• Experience presenting to senior leadership (A‑C level).
• Project management: managing multiple projects, meeting deadlines, working with minimal supervision.

Benefits

The Houston Chronicle named us a Top Workplace for the 10th consecutive year, based on employee survey responses covering company values, culture, leadership, and benefits. We are recognized for our values and the meaningful work we do.