Actuarial & Insurance AI Partner
Quick facts
- Pay
- $70–150 / hour
- Type
- Part-time
- Location
- Remote
- Platform
- Rex.Zone — 37 open jobs
- Typical pay at Rex.Zone
- $40–150/hour · median $95 (35 jobs on our site)
- Apply
- Free to apply — never pay to get AI training work
About the Role
As an Actuarial & Insurance AI Partner, your core mission is to ensure the actuarial logic of our AI models is sound and their risk assessments are accurate. Your expertise will be the foundation for building trustworthy and compliant AI solutions for the insurance industry.
Your contributions will include:
Evaluating AI Risk Models: Reviewing the logic and output of AI-generated models for pricing, reserving, and risk forecasting.
Annotating Claims Documents: Performing structured data extraction and labeling on unstructured documents like insurance claims and medical reports.
Validating AI-Powered Compliance Checks: Assessing the accuracy of AI systems in performing compliance checks during underwriting and claims processing.
Creating Complex Actuarial Scenarios: Designing and writing sophisticated scenarios for model stress testing and validation.
Who We're Looking For
A degree in Actuarial Science, Statistics, or Mathematics. Associate or Fellow-level actuarial credentials (e.g., ASA, FSA) are a major plus.
Experience in P&C, life, or health insurance with a background in pricing, underwriting, or reserving.
Proficiency in risk modeling and statistical analysis.
Exceptional attention to detail and an ability to work with complex rules and data.
Compensation
Compensation for our medical and financial experts typically ranges from $70 to $150 USD per hour, reflecting the critical nature and deep expertise required for these tasks. Rates at the higher end of this range are reserved for projects requiring highly specialized knowledge (e.g., niche surgical experience, complex financial instrument analysis) or extensive professional experience.
About Rex.Zone
Rex.Zone is the platform of RemoExperts, which hires remote professionals for AI training: data labeling, RLHF, and evaluation of large language models.