Applied Healthcare Researcher
Role overview
About the Company Protege is building a platform to facilitate the secure, efficient, and privacy-centric exchange of AI training data. Their DataLab team focuses on building and evaluating high-value datasets grounded in real-world workflows to solve the biggest unmet need in AI. Responsibilities Serve as the primary technical and research point of contact for healthcare customer conversations. Translate model-development goals into concrete, feasible data strategies. Develop and evaluate methods such as fine-tuning, LLM-based extraction, and classification to demonstrate dataset utility. Design and run feasibility research to determine if data can support specific model objectives. Build evidence bases including benchmarks, validation analyses, and error characterization. Evaluate healthcare data variables, labels, and cohort definitions for achievability. Identify proxy variables or alternative dataset structures when ideal variables are unavailable. Produce reusable research and technical collateral to scale successful workflows. Requirements Advanced degree (PhD or Master's plus 3+ years industry experience) in machine learning, computer science, biomedical informatics, epidemiology, statistics, or a related quantitative field. Hands-on experience building and evaluating ML or LLM-based systems for extraction, classification, or prediction. Experience working with healthcare data such as claims, EMR/EHR, clinical notes, or imaging. Proficiency in Python and SQL. Experience designing evaluations for data quality and dataset representativeness. Ability to work directly with technical stakeholders to translate ambiguous goals into research plans. Preferred Qualifications Experience working with messy, real-world clinical data. Ability to operate effectively on a customer's timeline. Interest in building reusable research frameworks rather than one-off solutions.
