ATTR 心脏淀粉样变性临床顾问（心脏病学家）

**Pay:** $120-$150 per hour (USD).

## 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 Cardiologist 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 and evidence-based reasoning.

## What You’ll Do

- Review patient charts and assess the likelihood of ATTR cardiac amyloidosis, including cases with incomplete information.

- Document clinical reasoning using specific, evidence-based criteria; distinguish ATTR from similar conditions and communicate uncertainty.

- Apply consistent labeling standards and refine assessments based on new evidence and AI model feedback.

- Explain clinical decisions clearly to engineers and data scientists and complete labeling batches within agreed timelines.

## Who Should Apply

- MD or DO with completed Internal Medicine residency and Cardiology fellowship.

- Currently practicing Cardiologist with **2+ years of post-fellowship experience**.

- Hands-on experience working up and managing patients with suspected or confirmed **ATTR cardiomyopathy**, including ordering and interpreting PYP scans.

- Strong preference for Heart Failure or Transplant Cardiologists with advanced heart failure experience, or specialists in amyloidosis or cardiomyopathies.

- Able to commit **10–20 hours per week** and translate complex clinical judgments into clear, structured criteria.

**Preferred:** Experience at amyloidosis center of excellence or cardiomyopathy clinic; publications on ATTR cardiomyopathy screening, epidemiology, or diagnostic pathways; or previous work with AI/ML teams, clinical decision-support systems, or clinical chart labeling.

## Project Details

- **Engagement:** Part-time consulting with a commitment of 10–20 hours per week.

- **Required Role:** US-based clinicians only.

- **Focus:** Patient chart annotation, clinical reasoning, and AI model improvement.