Senior Healthcare Data Labeling Specialist

About The Role

We're looking for experienced healthcare professionals to help shape the future of clinical AI. As a Senior Healthcare Data Labeling Specialist, you'll apply your domain knowledge to annotate and quality-review complex clinical datasets — directly influencing how AI systems understand and interpret real-world medical information. This is a fully remote, flexible contract role designed for clinicians, health informaticists, and healthcare data professionals who want to make a meaningful contribution to healthcare AI from wherever they work best.

What You'll Do

• Annotate complex clinical and electronic health record (EHR) data with precision and consistency
• Apply domain expertise to interpret and label nuanced medical terminology, diagnoses, procedures, and clinical narratives
• Perform quality assurance reviews on annotated datasets to ensure accuracy and adherence to guidelines
• Identify edge cases, ambiguities, and errors in clinical data and flag them with clear, structured feedback
• Follow detailed annotation guidelines while exercising sound clinical judgment
• Contribute to improving the overall quality and performance of healthcare AI models

Who You Are

• Background in healthcare, clinical informatics, nursing, medicine, health information management, or a related field
• Familiar with EHR systems and clinical documentation practices
• Strong attention to detail with a commitment to accuracy in every task
• Comfortable working independently and managing your own workflow
• Able to follow structured annotation guidelines consistently across large datasets
• Experience with medical coding (ICD, CPT, SNOMED) is a plus
• Prior data labeling or annotation experience is a plus, but not required

Nice to Have

• Experience with NLP, clinical NLP, or health informatics tools
• Familiarity with HIPAA and healthcare data privacy standards
• Background in clinical research, medical records, or health data quality

Why Join Us

• Work on meaningful AI projects that improve how technology understands clinical data
• Fully remote and asynchronous — work on your own schedule
• Freelance flexibility: autonomy, variety, and the ability to scale your hours
• Collaborate with a global team advancing cutting-edge healthcare AI
• Potential for ongoing work and contract extension based on performance