Member of Clinical Staff, Life Sciences
About The Position
Abridge is hiring a Clinician Scientist to lead the clinical science behind using clinical data generated by its ambient AI platform for research and life sciences applications. The role focuses on creating research-grade evidence from longitudinal clinical conversations, including trial feasibility and cohort identification, real-world evidence study design, endpoint definition, and quality standards that life sciences partners can trust. The Clinician Scientist will be embedded in the Life Sciences pod and work closely with ML Science, Product Management, Design, Legal/Privacy, and external research and pharmaceutical partners. The position requires working from Abridge’s San Francisco or New York City office at least three times per week. Relocation assistance is available for candidates willing to move to either city.
Requirements
- MD, DO, or equivalent clinical degree and at least 3 years of clinical practice experience.
- Working understanding of NLP, LLMs, prompt engineering, and model evaluation, with the ability to discuss evaluation methodology and quality measurement credibly with ML scientists.
- Ability to design scalable processes and frameworks rather than provide only one-off clinical input.
- Strong communication and influence skills, including presenting to technical, clinical, and external partner audiences and building trust across teams.
- Pragmatic, action-oriented approach; comfort with ambiguity and making progress when clinical or methodological gold standards do not exist.
Nice To Haves
- Board certification.
- Research and quantitative training, such as an MD/PhD, MD/MPH, or MD with a strong data science background.
- Experience in data science, medical affairs, clinical development, or research at a pharmaceutical or biotech company, or in a consulting role serving pharmaceutical companies.
- Experience with real-world data assets such as claims, registries, EHR-derived datasets, or trial data, including familiarity with their strengths and failure modes.
- Fellowship or advanced training in clinical informatics, pharmacoepidemiology, health services research, or biomedical informatics.
- Peer-reviewed publications in clinical trials, pharmacoepidemiology, or AI for healthcare.
- Programming ability in Python or SQL and comfort working with data, running analyses, or prototyping evaluation scripts.
- Experience at a health tech company, EHR vendor, or AI healthcare startup in a product or applied research role.
Responsibilities
- Serve as the clinical authority for Life Sciences products, including trial feasibility, cohort definition, real-world evidence, and research-facing outputs.
- Define endpoints and outcome measures that can be credibly derived from ambient data, and identify where the data cannot support a claim.
- Partner with ML Science to develop LLM judges, annotation frameworks, and evaluation pipelines for Life Sciences extraction tasks.
- Ensure evaluation methodologies reflect clinical and epidemiologic judgment.
- Translate between clinical and research realities and ML and engineering capabilities, clarifying clinical nuance, confounding, bias, and technical constraints.
- Act as a clinical counterpart for pharmaceutical, CRO, and academic partners; scope studies, shape feasibility assessments, and identify achievable and valuable work.
- Partner with Legal, Privacy, and Compliance on de-identification, consent, IRB pathways, and evidentiary standards for regulated research and healthcare.
- Bring partner and real-world usage insights into product direction, roadmap planning, and prioritization.
Benefits
- 14 paid holidays and flexible PTO for salaried employees; accrued time off for hourly employees.
- Medical, dental, and vision coverage for full-time employees and their families.
- Monthly HSA contributions for employees who choose a High Deductible Health Plan.
- Paid parental leave for full-time employees.
- Family-forming resources and financial support.
- 401(k) matching.
- Tax-free personal device allowance.
- Flexible Spending Accounts and commuter benefits.
- Monthly lifestyle wallet contributions for fitness, professional development, coworking, and more.
- Access to therapy and coaching.
- Paid sabbatical leave after 5 years of employment.
- Competitive compensation and equity grants for full-time employees.
- Relocation assistance for candidates willing to move to San Francisco or New York City.
- Flexible work hours and ongoing learning opportunities.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
Ph.D. or professional degree
