Healthcare AI Researcher — Data Strategy & Validation

Protege; New City (NY); On-site; USD 120,000 - 190,000; Full time

Job summary

Protege is seeking Applied Healthcare Researchers to join DataLab, focusing on healthcare training data. You will work directly with researchers at frontier labs and AI startups to identify data needed for training or evaluation and demonstrate its value on a customer timeline.

You will serve as the primary technical and research liaison, coordinating with solutions, engineering, and data partnerships to translate goals into rigorous data strategies and evaluations.

Qualifications

• Advanced degree in ML, CS, bioinformatics, epidemiology, or related field, or equivalent applied experience.
• Hands-on experience building and evaluating ML/LLM-based extraction, classification, or prediction on real-world data.
• Experience with healthcare data (claims, EMR/EHR, notes, imaging).
• Strong Python and SQL, able to work independently with large datasets.
• Experience designing evaluations for data quality and representativeness.
• Ability to translate ambiguous goals into concrete, defensible research plans.

Responsibilities

• Partner with researchers to translate model goals into data strategies.
• Develop and evaluate data methods to support training/evaluation objectives.
• Feasibility research pre-contract to assess data quality and caveats.
• Build evidence, benchmarks, and analysis for data strategy credibility.
• Collaborate cross-functionally with product and engineering.

Skills

ML/LLM systems

Healthcare data experience

Stakeholder communication

Independent data analysis

Education

PhD or MS + 3+ years

Tools

Python

SQL

Job description

Protege is seeking Applied Healthcare Researchers to join DataLab, focusing on healthcare training data. You will work directly with researchers at frontier labs and AI startups to identify data needed for training or evaluation and demonstrate its value on a customer timeline.

You will serve as the primary technical and research liaison, coordinating with solutions, engineering, and data partnerships to translate goals into rigorous data strategies and evaluations.