Senior Research Data Scientist

Abridge
NYC OfficePosted 19 March 2026

Tech Stack

Job Description

Senior Research Data Scientist ABOUT ABRIDGE Abridge was founded in 2018 with the mission of powering deeper understanding in healthcare. Our AI-powered platform was purpose-built for medical conversations, improving clinical documentation efficiencies while enabling clinicians to focus on what matters most—their patients. Our enterprise-grade technology transforms patient-clinician conversations into structured clinical notes in real-time, with deep EMR integrations. Powered by Linked Evidence and our purpose-built, auditable AI, we are the only company that maps AI-generated summaries to ground truth, helping providers quickly trust and verify the output. As pioneers in generative AI for healthcare, we are setting the industry standards for the responsible deployment of AI across health systems. We are a growing team of practicing MDs, AI scientists, PhDs, creatives, technologists, and engineers working together to empower people and make care make more sense. We have offices located in the Mission District in San Francisco, the SoHo neighborhood of New York, and East Liberty in Pittsburgh. THE ROLE Abridge is hiring a Senior Research Data Scientist to join our Strategic Research team. This role sits at the intersection of rigorous research, complex empirical data work, and deep cross-functional engagement with our commercial and builder organizations. You will be the team's resident expert on the data assets, structures, and pipelines that underpin our research — operating flexibly across the boundaries of data engineering, data analysis, and applied science to ensure the team can move quickly and confidently from raw data to credible insight. You will partner with research scientists to explore complex, messy real-world healthcare data: building and maintaining the data infrastructure the team depends on, developing and stress-testing metrics, conducting causal and descriptive analyses, and interrogating the assumptions embedded in our evaluation frameworks. You will work at startup pace with research rigor, with a mandate to go beyond off-the-shelf metrics and analyses to ensure that our evaluations capture what truly matters to clinicians and patients — not just what is easiest to measure. Equally important, you will translate complex analyses into clear, compelling narratives grounded in data, so that research insights inform product decisions, guide strategy, and help establish rigorous evidence for the real-world impact of ambient AI in healthcare. About Strategic Research. The Strategic Research team at Abridge has two primary functions: (i) designing and conducting rigorous research studies investigating the impact of ambient AI as an intervention in partnership with collaborating health systems; and (ii) conducting health care research that leverages Abridge data, and supporting external research efforts to do the same. In addition to driving and supporting empirical studies of the impact of ambient AI-enabled technologies, the team works closely with our Science and Engineering teams on core model evaluation. The common thread to all our work is ensuring that every partner-facing research initiative meets the highest standards of rigour, credibility, and strategic value. WHAT YOU'LL DO EVALUATION, MEASUREMENT, AND EMPIRICAL ANALYSIS - Conduct quantitative evaluations of Abridge models and products using data from real-world deployments, offline evaluations, and customer feedback - 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 - 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 ... (truncated, view full listing at source)
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