Senior Healthcare Data Labeling Specialist

Senior Healthcare Data Labeling Specialist (AI Training)
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.

• Type : Hourly Contract

• Location : Remote

- Commitment : Flexible hours

• Commitment : Flexible hours

• 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

• Contribute to improving the overall quality and performance of healthcare AI models

• 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

• Prior data labeling or annotation experience is a plus, but not required

• 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

• Background in clinical research, medical records, or health data quality

• 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