Healthcare Operations Professional - AI Trainer

About the Role DataAnnotation is seeking experienced healthcare operations professionals to join as contract contributors. In this role, you will apply your domain expertise to evaluate, annotate, and improve AI-generated responses related to healthcare operations, medical coding and billing, utilization management, and related subject matter. Your work directly shapes the accuracy and reliability of AI tools used by healthcare professionals every day. Key Responsibilities Review and evaluate AI-generated responses to healthcare operations-related prompts for accuracy, clarity, and professional appropriateness Annotate and rank model outputs to guide AI training and improvement Write clear, expert-level answers to healthcare operations questions that serve as model training examples Flag errors, misconceptions, or ambiguous outputs and provide corrective guidance Maintain consistent quality and throughput throughout the sprint engagement Compensation & Terms Pay is $50-$100+/hr, with bonus rates available on some projects Paid on a regular cadence; contract position Fully remote — work from anywhere in the US Notes Work on DataAnnotation projects on a flexible, project-by-project basis — choosing what to work on, when, and at whatever cadence fits your schedule. What to Expect DataAnnotation believes that human expertise is essential to building trustworthy AI. We don’t want AI training AI — we want real professionals in the room. If you have a strong healthcare operations background and want to put it to work in a new way, we’d love to hear from you. Qualifications Demonstrated healthcare operations experience (medical coding and billing, health information management, utilization review, healthcare administration, or similar) Medical coding certification (e.g., CPC, CCS) not required, though preferred - practical expertise matters more than credentials Strong written communication skills; ability to explain complex concepts clearly and concisely Comfortable working independently in a remote, self-directed environment Based in the United States Has a general understanding of LLM use/ the AI landscape #J-18808-Ljbffr Sustainable World, Inc.