Applied Healthcare Researcher

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.