AI Insurance Tutor
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Role Description
Mercor is partnering with a leading AI research organization to engage professionals with advanced expertise in insurance analysis, actuarial science, and data evaluation. As an AI Insurance Data Specialist , you will play a key role in enhancing next-generation AI models by providing expert annotations and structured data tailored to real-world insurance applications. Your work will directly influence how AI systems understand and reason about insurance operations, including areas such as risk assessment, actuarial modeling, claims adjustment, and policy evaluation. This is a full-time opportunity for individuals with a deep understanding of insurance data, strong analytical judgment, and a passion for innovation in AI-driven technologies.
Key Responsibilities
- Use proprietary software to label and annotate insurance-related data, ensuring accuracy and consistency for AI model development
- Curate and deliver high-quality datasets for actuarial, claims, and risk assessment scenarios
- Collaborate with technical teams to improve annotation workflows and enhance model training tools
- Identify and solve complex problems in insurance analytics to improve AI performance and accuracy
- Design and refine efficient data collection and labeling systems for insurance datasets
- Interpret and execute evolving task guidelines with precision, adaptability, and independent judgment
Qualifications
- Professional experience in insurance or a related field such as actuarial analysis, risk management, or claims processing
- Proficiency in both informal and professional English writing and communication
- Strong analytical, organizational, and problem-solving skills with the ability to work independently
- Demonstrated ability to interpret complex instructions and ensure data precision
- Deep interest in the intersection of technology, data, and insurance innovation
Preferred Background
- Professional certifications such as Associate or Fellow of the Society of Actuaries (ASA/FSA) or Chartered Property Casualty Underwriter (CPCU)
- Experience mentoring or training others in insurance-related practices
- Familiarity with AI, data annotation tools, or machine learning workflows
- Comfort with recording short audio or video sessions for data training purposes
Work Environment & Requirements
- This role is based in Palo Alto, CA (in-office, 5 days per week) or may be performed remotely with strong self-management skills
- Work schedule: 9:00am–5:30pm PST during training, then local timezone thereafter
- U.S.-based applicants must reside outside of Wyoming and Illinois
- Visa sponsorship is not available
- Required equipment: Chromebook, Mac (macOS 11+), or Windows 10+ device with reliable smartphone access
Compensation
- Competitive pay ranging from $90,000 to $200,000 annually for U.S.-based professionals, depending on experience and location
- International pay ranges available upon request
- Compensation packages may include additional benefits based on location
Application Process
- Submit your resume to begin the application process
- Join a 20-minute initial interview to discuss your background and qualifications
- If selected to advance, you’ll move on to a technical discussion focused on insurance data, actuarial methods, and annotation experience
- Complete a short take-home assessment centered on data labeling or analytical problem-solving
- Conclude with a final conversation with the broader project team
- The full interview process is typically completed within one week