Senior Research Data Scientist

Abridge · Vertical AI · New York, NY · Builder

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.

What you'd actually do

  1. Conduct quantitative evaluations of Abridge models and products using data from real-world deployments, offline evaluations, and customer feedback
  2. Develop and validate metrics that reflect meaningful outcomes for providers and patients — including assessing construct validity, characterizing measurement error, and surfacing selection bias in observational signals like user ratings and feedback
  3. Design and execute analyses that address the team's core research questions: validating automated evaluation frameworks against human judgment, characterizing heterogeneity in adoption and usage trajectories, estimating causal effects of ambient AI on clinical and operational outcomes, and extracting structured characterizations of clinical practice from unstructured conversation data
  4. Build deep familiarity with existing metrics and evaluation frameworks used at Abridge and beyond, interrogating underlying assumptions and proposing alternatives where appropriate
  5. Develop and maintain deep expertise in Abridge's data assets — including production data, user feedback signals, and clinical conversation data — and serve as the team's authority on data provenance, structure, and limitations for research studies

Skills

Required

  • SQL
  • Python or R
  • building or working closely with data pipelines and data infrastructure
  • data science experience in healthcare

What the JD emphasized

  • rigorous research
  • complex empirical data work
  • deep cross-functional engagement
  • research rigor
  • go beyond off-the-shelf metrics and analyses
  • highest standards of rigour, credibility, and strategic value
  • quantitative evaluations
  • develop and validate metrics
  • address the team's core research questions
  • interrogating underlying assumptions
  • deep expertise in Abridge's data assets
  • authority on data provenance, structure, and limitations
  • build, extend, and maintain the data pipelines
  • ensure that the data the research team needs is accessible, reliable, and well-understood
  • ensure evaluation and analysis are credible, decision-relevant
  • grounded in a deep understanding of product development and integration
  • ensure measurement and evaluation reflect how products are used and experienced in real-world practice
  • translate complex analyses into clear, nuanced narratives grounded in data
  • produce technical analyses, reports, and presentations that inform product decisions, guide strategy, and contribute to a rigorous evidence base

Other signals

  • evaluating AI models
  • measuring AI impact
  • data infrastructure for research
  • translating research into product decisions