Senior Research Data Scientist at Abridge, focusing on evaluating AI models and products in healthcare. The role involves developing and validating metrics, conducting quantitative evaluations, building data infrastructure for research, and communicating insights to inform product decisions and strategy. It emphasizes rigorous research and data expertise to measure the real-world impact of ambient AI.

Research Scientist focused on evaluating and advancing the real-world impact of ambient AI in healthcare. This role involves designing and leading empirical studies, operationalizing complex constructs using rigorous measurement frameworks, and developing evaluation frameworks to inform model development and product strategy. The work directly contributes to understanding how AI systems affect patients and providers, with a strong emphasis on rigorous evaluation and measurement.

Product leader to define the vision, strategy, and execution for Abridge's core note generation models and evaluation stack. This role will manage a team of PMs and partner with engineering, ML, design, and clinical leaders to set the bar for note quality, guide the model and evaluation roadmap, and deliver key capabilities for the market. The role emphasizes leading AI product strategy, overseeing the evaluation platform and measurement systems, driving depth across specialties, and leading/developing a team of PMs.

Abridge is seeking a Head of Clinician Science to lead a team responsible for ensuring the clinical validity and meaningfulness of their AI-powered healthcare platform. This role bridges clinical expertise with AI/ML development, focusing on defining quality standards, building scalable evaluation systems, and translating clinical workflows into product requirements. The ideal candidate has a strong clinical background, management experience, and technical fluency with AI/ML, particularly NLP and LLMs.

Senior Data Scientist at Abridge, a healthcare AI company, focused on driving product strategy through data analysis, user behavior modeling, A/B testing, and AI model evaluation. The role involves ensuring visibility into AI generation pipelines and investigating issues, with a critical need for data to drive user engagement and retention. Collaboration with product, engineering, and science teams is key.