Forward Deployed Data Scientist
AI summary of the role
First Forward Deploy Data Scientist at a Series-A healthcare AI startup, working directly with health system customers to turn messy clinical data into ML-ready pipelines and insights.
What you’ll do
- Partner directly with health systems and hospital customers to understand data, workflows, and goals, sharing data insights that demonstrate product value.
- Design and execute data and ML investigations, validating and transforming large structured and unstructured healthcare datasets with state-of-the-art models.
- Deploy, build, and operationalize ML and LLM-based models and analytics pipelines with engineering and product teams.
- Work with customer success and product teams to improve user engagement through data-driven analyses.
What you’ll bring
- 2-3 years of professional experience in data science.
- Strong programming skills in Python and fluency with modern data science and ML/NLP libraries (PyTorch, TensorFlow, HuggingFace).
- Experience with ML Ops tools (Airflow, MLflow, dbt, Docker, or cloud ML platforms).
- Familiarity with modern applied LLM techniques and their practical implementations.
Technologies
Python · PyTorch · TensorFlow · HuggingFace · Airflow · MLflow · dbt · Docker · LLM · NLP
About Layer Health
LLM chart-review platform for health systems and life-sciences teams, extracting reliable evidence from longitudinal medical records for registries, quality, research, and pathways.
Series A · 10–50 people
Source and classification
Internal deployment & tooling · Evidence for this classification:
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. What you'll do: Partner directly with health systems and hospital customers to understand their data, workflows, and goals, sharing data
More from the 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. Here’s a collection of articles about our product, mission, recent funding round, etc. Job Description 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 [... source excerpt omitted ...] 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. What you'll do: 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 pipelin [... source excerpt omitted ...] esults 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. We look for: 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
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