Research Scientist (measurement and Evaluation)

Abridge · Vertical AI · New York, NY · Builder

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.

What you'd actually do

  1. Design and conduct evaluations of Abridge models and products
  2. Engage with external researchers and other stakeholders on designing and conducting research on ambient AI and research that leverages Abridge data
  3. Develop a strong user-centric and patient-centric mindset, grounding the research in empathy for the real world experience of providers and patients
  4. Collaborate across our cross-functional product teams to ensure the research is deeply informed by current practices and our product roadmap
  5. Write technical reports and give presentations to internal and external stakeholders

Skills

Required

  • PhD in statistics, biostatistics, computer science, economics, information systems, clinical informatics, or a related field
  • Expertise in rigorous quantitative or mixed-methods approaches for conducting evaluations using observational and experimental data
  • Strong research track record in evaluation and measurement, as evidenced by high-impact publications at peer-reviewed journals or conferences
  • A problem-before-method mindset
  • A curious, adaptable, and proactive mindset

Nice to have

  • Mentoring research interns
  • Relocation assistance

What the JD emphasized

  • rigorous evaluation
  • rigorous experimental or quasi-experimental methods
  • rigorous quantitative or mixed-methods approaches
  • rigorous research studies
  • highest standards of rigour, credibility, and strategic value
  • rigorous quantitative or mixed-methods approaches for conducting evaluations using observational and experimental data
  • strong research track record in evaluation and measurement
  • high-impact publications at peer-reviewed journals or conferences
  • problem-before-method mindset
  • push the methodological frontier

Other signals

  • design and lead empirical studies of Abridge models and products
  • 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
  • develop evaluation frameworks that inform model development and product strategy