Create realistic insurance questions and case studies, then assess whether AI responses are accurate, complete, and consistent with industry standards. You will turn practical insurance knowledge into clear challenges that test how well AI applies complex principles.
- Develop questions and case studies on underwriting, claims adjudication, policy interpretation, risk assessment, regulatory compliance, and actuarial principles.
- Design scenarios that test how AI interprets and applies insurance concepts.
- Review model responses for accuracy, completeness, and alignment with insurance standards and best practices.
- Give detailed feedback to improve model performance and content quality.
- Work with insurance and technical specialists to set question difficulty and keep training content challenging and educational.
Pay, schedule, and qualifications
- Pay: $80 per hour.
- Schedule: Flexible and asynchronous, with a 20+ hour weekly commitment.
- Location: Remote; open to candidates in the countries listed for this role.
- Language: Professional fluency in English.
- Education: A bachelor's degree in risk management, finance, business, or a related field, or equivalent professional experience.
- Experience: Professional experience in insurance operations, underwriting, claims management, or risk assessment.
- Skills: Strong knowledge of insurance products, industry practices, and real-world risk decisions, plus strong analytical, written, and verbal communication skills and close attention to detail.
- Helpful background: Experience in multiple insurance lines, such as property and casualty, life and health, or commercial insurance; work in insurance publications, regulation, or insurtech; or designations such as CPCU, CLU, ChFC, ARM, or AINS. Familiarity with technology-driven insurance applications is also useful.
How to apply
Apply on OpenTrain with your resume, then complete the application on the hiring site. Creating an OpenTrain account is free.
About AI training work
AI training is the human work behind AI: people create examples and evaluate answers so models can learn. Insurance specialists are paid to bring practical knowledge to challenging scenarios and judge whether AI responses meet industry standards.