Insurance Risk Analyst - Fully Remote

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

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