Job Description
Healthcare AI that gets things wrong does not just frustrate users — it can compromise patient safety. Chegg is seeking professionals with deep backgrounds in hospital data management and clinical compliance to serve as Consultants in our AI training programme. You will validate AI outputs against real healthcare governance standards, flag compliance risks, and deliver the precise feedback that keeps our models safe and accurate. Fully remote and asynchronous.
Core Responsibilities
- Examine hospital health records and AI-generated clinical documentation for accuracy, completeness, and conformance with established data governance standards
- Pinpoint gaps, inconsistencies, and regulatory exposure in healthcare data structures, workflow descriptions, and governance control documentation
- Apply HIPAA, HL7, and related compliance frameworks to assess whether AI-generated policies and data-handling guidance reflect genuine regulatory requirements
- Critique AI outputs on clinical data classification, record-keeping practices, and patient-data governance — providing structured corrective feedback
- Bring integrated clinical, IT, and compliance expertise to bear when judging the practical soundness of AI recommendations
Key Qualifications
- Experience in a hospital or integrated health system in a data governance, clinical data management, or health information operations capacity is a plus but not required
- Thorough command of HIPAA compliance and related healthcare privacy standards as applied to real clinical workflows
- Skilled at assessing data quality simultaneously across clinical, operational, and administrative domains
- Systematic, meticulous reviewer — notices when data standards are not met and articulates findings precisely in writing
Nice to Have
- Hands-on background with EHR platforms such as Epic, Cerner, or Meditech
- Familiarity with HL7 FHIR or other interoperability standards
- Advanced credentials in health information management — RHIA or CPHIMS
Why Chegg
- Fully remote and flexible
- Task-based commitment — typically 10–40 hours per week
- High-stakes, high-impact AI work in the healthcare domain
- Ongoing project opportunities for strong contributors