Job Description

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.

Job Description

We’re hiring an exceptional data scientist to join our team (Boston or NYC office). In this role, you will be responsible for advancing our applied ML and data science capabilities for healthcare.

Responsibilities

• Develop, validate, and measure the impact of large language model (LLM) and other ML-based approaches for chart abstraction from both unstructured and structured healthcare data.
• Apply and rigorously evaluate cutting‑edge methods to solve real clinical problems.
• Work hand‑in‑hand with our customers to best leverage Layer Health’s platform and supercharge their workflows.
• Stay up‑to‑date on the latest in applied NLP and generative AI techniques and proactively explore these technologies where applicable.
• Establish and enforce best practices for data science and analytics.
• Cultivate and foster a robust and thoughtful data science and product culture that drives the company forward.

Qualifications

• 5‑7+ years of professional experience as a data scientist working for a company with major ML dependencies.
• At least 3‑4 years of healthcare / clinical applications experience.
• A solid foundation of ML/methods.
• Fluent programming skills in Python, and fluency with modern data science and ML/NLP libraries (PyTorch, Tensorflow, HuggingFace, etc.).
• Deep fluency and instincts for data manipulation, treatment, and evaluation, with the ability to wrangle large, complex datasets efficiently and methodically.
• Familiarity with modern applied LLM techniques and their practical implementations (any experience using these techniques is a bonus).
• Proactive mindset to identify and solve problems, continuously improving our data science capabilities.
• A strong communicator who thrives in a customer‑focused, fast‑paced environment.
• An excited and adaptable team player who wants to disrupt the healthcare industry with AI/ML, alongside an awesome team.
• We are a Boston‑based company, and expect engineers to meet regularly in‑person in Boston (engineers from Boston, NYC, or east coast are welcome).

Compensation

Expected compensation range for this role is $190,000 - 220,000. Compensation is dependent on experience, overall fit to our role, and candidate location. Expected compensation ranges for this role may change over time. If your compensation requirement is greater than our posted salary ranges, please still consider applying to our role. We will make a determination as to whether an exception can be made.

Application Note

If you are excited about this role, we encourage you to apply even if you don’t feel you meet every single requirement. We’re eager to meet people that believe in our mission and can contribute to our team in a variety of ways. We welcome diverse perspectives, rigorous thinking, and fearlessness in challenging the status quo.

Equal Opportunity Employer

Layer Health is committed to fostering an environment of inclusion that is free from discrimination. We are an Equal Opportunity Employer where employment is decided on the basis of qualifications, merit, and business need. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected Veteran status, or any other characteristic protected by law.

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