Forward Deploy Data Scientist

Layer Health was founded in 2023 by leading machine learning researchers from MIT and Harvard Medical School. We are building an AI layer that can accurately and scalably synthesize information from medical records, with the mission to reduce friction everywhere in healthcare. Our LLM-powered platform is solving chart review once and for all, across use cases. For health systems, our first product dramatically accelerates clinical registry abstraction in areas ranging from surgery and cardiology, to oncology.

Our long term vision is for our AI layer to safely transform patient care and minimize unnecessary heartbreak. Layer Health’s diverse founding team brings expertise across machine learning, UI/UX, large language models, and medicine.
Here’s a collection of articles about our product, mission, recent funding round, etc.

We’re hiring our first Forward Deploy Data Scientist. You’ll work directly with customers and internal teams to translate messy healthcare data into actionable insights and machine learning-ready pipelines. You’ll work hand-in-hand with our world-class ML and broader engineering team, as well as our product and customer success teams.
You’ll partner with our health systems & hospital IT/data teams, as well as internal Customer Success Managers, product managers and software engineers to validate data pipelines, share insights, and ensure our solutions deliver measurable value in clinical and operational workflows. This is a hands-on, high-impact role - ideal for someone who loves working with data, solving ambiguous problems, and collaborating across technical and non-technical stakeholders.

• Partner directly with health systems and hospital customers to understand their data, workflows, and goals, sharing data insights that enable our customers to understand our product value and areas of opportunity.
• Design and execute data and ML investigations - validating, and transforming large structured and unstructured healthcare datasets with state of the art models to ensure accuracy and trustworthiness.
• Deploy, build, and operationalize ML and LLM-based models and analytics pipelines in collaboration with the broader engineering and product teams.
• Work hand-in-hand with customer success and product teams to understand and improve user engagement through data-driven analyses.
• Communicate results and insights clearly to technical, product, and clinical stakeholders.
• Build reusable playbooks, tools, and best practices to accelerate future implementations and improve customer outcomes.
• Stay current on emerging ML, NLP, and healthcare data technologies and proactively apply them to real-world clinical problems.
• Contribute to a culture of collaboration, innovation, and rigor across the data science and product teams.

• 2-3 years of professional experience in data science (a proven track record of successful projects in healthcare or clinical applications is a bonus, but not required).
• A strong communicator who thrives in a customer-focused, fast-paced environment - must be comfortable presenting to external customers and have a partnered/strategic mindset.
• Strong programming skills in Python, and fluency with modern data science and ML/NLP libraries (PyTorch, Tensorflow, Hugging Face, etc.).
• Experience with ML Ops tools (Airflow, MLflow, dbt, Docker, or cloud ML platforms).
• Familiarity with modern applied LLM techniques and their practical implementations (any experience using these techniques is a bonus).
• Deep fluency and instincts for data manipulation, treatment, and evaluation, with the ability to wrangle large, complex datasets efficiently and methodically.
• Proactive mindset to identify and solve problems, continuously improving our data science…