Data Scientist

🏢 Layerhealth · 📍 Boston or NYC 💰 $180,000 - $180,000 / yr

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Position Summary & Responsibilities

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.

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.

You can expect to:

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.

We look for:

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 larg

🎯 Candidate Preparation Guide For Layerhealth Applicants

Key Role Competencies & Evaluation Highlights

Key Role Focus:

Strict evaluation centers on healthcare data interoperability, strict clinical data privacy standards (HIPAA/PHI), and enterprise AI integration.

📋 Preparation Priorities (Key Areas to Clarify):

1. Proposing move-fast-and-break-things engineering approaches that compromise healthcare data privacy or regulatory compliance.
2. Superficial understanding of clinical workflows and administrative friction points in hospitals.
3. Inability to explain complex technical medical data pipelines to non-technical clinical stakeholders.

✨ Recommended Role Alignment Hook:

I build secure, interoperable health data infrastructure that empowers clinical teams without ever compromising patient privacy.

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