Role brief
Job description
## About the Role
An AI healthcare company that automates administrative and pharmacy workflows to help patients access life-changing medications and specialty treatments is seeking an experienced Cardiology Nurse Practitioner (NP), Registered Nurse (RN), or Physician Assistant (PA) for a part-time consulting role. The role focuses on improving an AI model that identifies patients likely to have **transthyretin (ATTR) cardiac amyloidosis** through clinical chart review, patient case labeling, and evidence-based clinical reasoning.
## What You’ll Do
– Review patient charts and assess the likelihood of ATTR cardiac amyloidosis, including cases with incomplete information.
– Identify relevant clinical signals, including patient history and diagnostic findings such as PYP scans, where applicable.
– Document clear, evidence-based reasoning; distinguish ATTR from similar conditions and maintain consistent labeling standards.
– Refine assessments based on new evidence and AI model feedback, explain clinical decisions to technical teams, and meet labeling deadlines.
## Who Should Apply
– NP, RN, or PA with **5+ years of cardiology-focused experience**, ideally within a cardiology practice or clinic.
– **1–3 years of experience** in a Heart Failure or ATTR-specific clinic.
– Hands-on experience evaluating or managing suspected or confirmed ATTR cardiomyopathy, including PYP scans as appropriate to professional scope.
– Strong clinical judgment and the ability to explain decisions using clear, structured criteria.
– Able to commit **10–20 hours per week** alongside clinical practice.
**Preferred:** Experience at amyloidosis center of excellence or cardiomyopathy clinic; contributions to ATTR-related research or publications; or prior experience with AI/ML teams, clinical decision-support systems, or clinical chart abstraction and labeling.
## Project Details
– **Engagement:** Part-time with a commitment of approximately 10–20 hours per week.
– **Required role**: US-based clinicians only
– **Focus:** Patient chart annotation, clinical reasoning, and AI model improvement.