Mercor is partnering with a leading AI lab to train frontier models on high-quality insurance reasoning data. We're hiring P&C Actuaries and Portfolio Risk Managers to design realistic pricing, reserving, forecasting, and portfolio-management scenarios, evaluate model outputs against established actuarial standards, and help shape how the next generation of AI reasons quantitatively about insurance risk.
We welcome pricing actuaries, reserving actuaries, portfolio analysts, catastrophe-risk professionals, and actuarial managers from carriers, reinsurers, MGAs, and consulting firms.
Design realistic scenarios involving loss costs, rate indications, trend, development, credibility, segmentation, reserving, profitability, capital, catastrophe exposure, and portfolio concentration
Create work products such as pricing analyses, reserve reviews, portfolio diagnostics, assumption critiques, sensitivity analyses, and management recommendations
Write "golden" reference responses at experienced actuarial and portfolio-risk quality
Grade AI-generated responses against structured rubrics for mathematical accuracy, assumption quality, methodology, interpretation, and communication
Identify calculation errors, unsupported assumptions, misuse of actuarial methods, confusing correlation with causation, and recommendations not supported by the data
Provide written feedback the research team uses to improve model behavior
Participate in onboarding office hours and calibration sessions
Have 2+ years of professional experience in P&C actuarial work, insurance pricing, reserving, catastrophe modeling, or portfolio risk management
Have performed quantitative analysis using insurance premium, exposure, claim, loss, or reserve data
Understand the difference between account-level underwriting judgment and portfolio-level actuarial analysis
Can explain methods, assumptions, limitations, and business implications clearly to technical and nontechnical audiences
Demonstrate strong quantitative reasoning, excellent written communication, and high attention to detail
Are proficient with spreadsheets and at least one analytical or statistical tool
ACAS, FCAS, or active progress toward CAS credentials
Experience with personal, commercial, specialty, or reinsurance portfolios
Catastrophe modeling, capital modeling, predictive modeling, or rate-filing experience
Proficiency with SQL, R, Python, SAS, or actuarial modeling platforms
Experience presenting results to underwriting, finance, claims, or executive stakeholders
Minimum 20 hours per week (ideally 40+)
Role starts immediately, applications reviewed on a rolling basis