Member of Technical Staff (Research Science)

Join Abridge, a high-growth startup focused on advancing the real-world impact of ambient AI on patient outcomes, care quality, and provider experience. As a Research Scientist, you will design and lead empirical studies, operationalize complex constructs, and develop evaluation frameworks. Your work will contribute to the broader scientific understanding of how AI systems affect patients and providers. Enjoy unlimited PTO, flexible working hours, equity, and a remote work environment.

• Design and lead empirical studies of Abridge models and products in partnership with health systems, leveraging large-scale clinical conversation data.
• Operationalize complex constructs—such as quality of care, safety, cognitive burden, and return on investment—using principled measurement frameworks and rigorous experimental or quasi-experimental methods.
• Collaborate across cross-functional product teams to ensure the research is deeply informed by current practices and our product roadmap.

• Strong judgment about clinical data and study design: you recognize when an outcome is poorly measured, a study is confounded, or an evaluation does not support the intended clinical claim
• MD, PhD, or equivalent research background. Relevant PhD fields include computer science, biomedical or clinical informatics, statistics, biostatistics, and related disciplines. Physician applicants should bring substantial quantitative or computational research experience; a PhD is not required
• 3+ years of research experience within clinical environments or through sustained collaboration with clinicians and health systems. This experience may include, but is not limited to, work conducted during research or clinical training
• The ability to lead substantive scientific discussions with experienced clinical investigators and researchers, explain methodological tradeoffs clearly, and build productive collaborations
• A strong record of leading rigorous research in clinical informatics, AI in healthcare, or related fields, demonstrated through peer-reviewed publications in top venues and clear ownership of the underlying work
• Rigor at speed. You can scope and execute scientifically rigorous work under compressed timelines. You make thoughtful tradeoffs to deliver credible evidence where and when it is needed most
• A problem-before-method mindset. You do not change the question to make it amenable to simple analysis. You use established methods when they are sufficient, learn unfamiliar approaches when needed, and develop new methods when existing ones fall short