Data Science Team Lead / LLM / Digital Health

One of our clients, a rapidly growing digital health SaaS company, is looking to hire a Data Science Team Lead. This company is on a mission to revolutionize how physicians interact with patient data by using advanced AI technologies. Their platform helps clinicians across the U.S. by turning fragmented and complex medical data into clear, actionable insights that can be used in real time at the point of care.

Their solution is already being used by thousands of physicians and is helping reduce burnout, prevent missed diagnoses, and improve overall patient care.

The company has received international recognition, having been named one of the Top 100 AI companies globally and ranked among the Top 50 Digital Health startups. Their clientele includes leading value-based healthcare organizations.

This is a hands-on leadership role in a core R&D team working on AI/ML and NLP-focused products. The ideal candidate will have significant experience in machine learning and natural language processing (NLP), particularly in applying these in production environments. You will manage a team of five data scientists, lead the design and deployment of scalable ML pipelines, and contribute to shaping the direction of the company’s data science strategy.

Key Responsibilities:

• Lead and mentor a team of algorithm researchers and data scientists.
• Own projects from early research through production deployment.
• Guide the development of advanced models and services with real-world clinical impact.
• Design scalable machine learning and NLP pipelines.
• Collaborate closely with engineering and product teams.

Requirements:

• B.Sc and M.Sc in Computer Science, Engineering, Bioinformatics, or a related field.
• 5+ years of industry experience in Data Science with a strong emphasis on NLP.
• At least 2+ years of experience in a team leadership or technical mentorship role.
• High proficiency in Python and software engineering practices.
• Hands-on experience building, deploying, and maintaining ML systems at scale.
• Deep understanding of NLP techniques (language models, embeddings, QA, etc.).
• Experience designing batch and real-time ML architecture in production.

Advantages:

• Ph.D. in a relevant field.
• Experience with cloud environments and infrastructure (AWS, Docker, Kubernetes).
• Experience working with Large Language Models (LLMs) in production.
• Familiarity with MLOps tools and practices (e.g., SageMaker, annotation tools, experiment tracking).

Number of employees: 150