Clinical Quality Data Abstraction Specialist - GWTG (Contractor)

Remote

About the role

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 building a team of clinical abstractors for our GWTG work (specifically focused within Stroke and Heart Failure). This is a remote (US only) part time (~15 hours per week) contractor opportunity.

What you'll do Assist with case abstraction under the direction of a Team Leader Complete assigned abstractions in a timely manner As a start up organization, roles and

responsibilities often evolve and adapt over time. As such, this job description may not comprehensively account for future activities,

responsibilities, and priorities—these may evolve right along with us! What you'll need 1+ years abstraction within the GWTG Stroke or Heart Failure Registry (this is a 100% requirement) Exposure to multiple patient medical record systems (EMRs) and clinical databases. Ability to thrive in a fast and ever-changing environment. Expected

compensation range for this role is $28-35/hour and this is a part time contractor role for ~15 hours per week.

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. If you are excited about this role, we encourage you to apply even if you don't feel that 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. Join us and help us transform healthcare with AI. Layer Health is committed to foster 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.

About Layer Health

Layer Health is a health technology company that utilizes AI and large language models to streamline medical chart reviews. Layer Health's AI platform uses large language models (LLMs) trained on extensive patient data over time. This technology enables healthcare systems to analyze and interpret both structured and unstructured clinical information with an accuracy comparable to that of clinicians. In contrast to conventional software solutions that predominantly depend on fixed rules, Layer Health’s AI operates with a reasoning approach akin to that of a clinician, allowing it to navigate highly nuanced and intricate situations throughout a patient's complete medical record.

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Job details

Salary

$58,240 - $72,800

Location

Remote

Company

NameLayer Health
IndustryAnalytics
Team Size2

Funding

Total raised

$33.5M

Last stage

Series A

Investors

DDefine Ventures
GV (Google Ventures)
General Catalyst
Flare Capital Partners
MMultiCare Capital Partners

Founders

Monica Agrawal

Monica Agrawal

Co-Founder & Head of Research

LinkedIn
DG

Divya Gopinath

Co-Founder & Co-Head of Engineering

David Sontag

David Sontag

Co-Founder & CEO

LinkedIn
SH

Steven Horng

Co-founder & VP of Clinical Informatics

What happens next.

No applications, no recruiter spam. Just the intro.

01

Confirm the fit

A few questions to make sure this role is the right shape for you. Two minutes.

02

I pitch you to the company

I write the intro, send it to the founder, and handle the back-and-forth.

03

A meeting lands on your calendar

If they’re a yes, I book the chat. You show up — that’s the whole job-hunt.