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Layer Health

AI platform for clinical chart review

Forward Deployed Data Scientist

Applied Machine LearningUpdated on Nov 10
Full-time$150k - $180k

About the Job

Requirements

  • Have 2–3 years of professional experience in data science.
  • Be comfortable presenting to external customers in a customer-focused environment.
  • Have strong programming skills in Python and fluency with modern data science and machine learning/natural language processing libraries such as PyTorch, TensorFlow, and Hugging Face.
  • Have experience with machine learning operations tools such as Airflow, MLflow, dbt, Docker, or cloud machine learning platforms.
  • Be familiar with modern applied large language model techniques and their practical implementations.
  • Have strong data manipulation, treatment, and evaluation skills, and be able to efficiently and methodically work with large, complex datasets.
  • Be willing to work hybrid with the team in a Boston or New York City office 2–3 days per week.

Responsibilities

  • Partner directly with health systems and hospital customers to understand their data, workflows, and goals, and share data insights that help customers understand product value and opportunities.
  • Design and execute data and machine learning investigations by validating and transforming large structured and unstructured healthcare datasets with state-of-the-art models to ensure accuracy and trustworthiness.
  • Deploy, build, and operationalize machine learning and large language model-based models and analytics pipelines with the broader engineering and product teams.
  • Work with customer success and product teams to understand and improve user engagement through data-driven analyses.
  • Communicate results and insights 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 machine learning, natural language processing, and healthcare data technologies and apply them to real-world clinical problems.
  • Contribute to collaboration, innovation, and rigor across the data science and product teams.

Desired Qualifications

  • Healthcare or clinical application project experience.
  • Experience using modern applied large language model techniques.
  • Familiarity with Epic, Cerner, or other electronic health record systems.
  • Experience in forward-deployed, field data science, or consulting-style roles.
  • Background in artificial intelligence/machine learning for healthcare, clinical analytics, or real-world data.

About the Company

Layer Health

AI platform for clinical chart review

Layer Health builds an enterprise AI platform for healthcare chart review. It uses a healthcare-focused large language model (LLM) to analyze longitudinal patient charts, enabling clinicians and life sciences teams to answer complex clinical questions, automate clinical registries, and generate quality measurements. The system works by processing patient charts through modules that support registry data submission, real-world evidence abstraction, and patient registries, with emphasis on accuracy, configurability, and security. It differentiates itself from competitors through healthcare-specific validation, enterprise-grade security/compliance, and a broad set of use cases tailored to both health systems and life sciences, enabling faster, more reliable data analysis with fewer administrative burdens. Its goal is to streamline chart review, improve data quality, and free clinicians to focus more on patient care by delivering actionable insights and reliable data faster.

Company size
51-200
Company stage
Series A
Total funding
$25M
Headquarters
Boston, MA
Founded
2023

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