P&C Actuary - Risk Management - AI Trainer

About the Role 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. What You'll Do 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 You're a Good Fit If You 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 Bonus Qualifications 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 Role Highlights Minimum 20 hours per week (ideally 40+) Role starts immediately, applications reviewed on a rolling basis #J-18808-Ljbffr Mercor