P&C Actuary & Portfolio Risk Manager

Posted Yesterday
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6 Locations
Remote
80-80 Hourly
Junior
Artificial Intelligence • HR Tech • Professional Services • Software
The Role
Design insurance pricing, reserving, forecasting, and portfolio-risk scenarios for AI model training. Create actuarial analyses and reference answers, evaluate AI outputs for quantitative and methodological accuracy, identify unsupported assumptions and errors, and provide structured feedback. The role requires explaining actuarial methods and business implications to technical and nontechnical audiences while participating in calibration and onboarding sessions.
Summary Generated by Built In

This role is for one of our clients

Compensation: $80 per hour

We are 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.


Requirements

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

We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.

Skills Required

  • 2+ years of professional experience in P&C actuarial work, insurance pricing, reserving, catastrophe modeling, or portfolio risk management
  • Quantitative analysis experience using insurance premium, exposure, claim, loss, or reserve data
  • Understanding of account-level underwriting judgment versus portfolio-level actuarial analysis
  • Ability to explain methods, assumptions, limitations, and business implications clearly to technical and nontechnical audiences
  • Strong quantitative reasoning, excellent written communication, and high attention to detail
  • Proficiency 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
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The Company
Year Founded: 2021

What We Do

Weekday is an AI-powered recruitment platform that helps startups hire top-tier engineering and product talent. By leveraging a massive database of white-collar professionals and advanced outreach tools, the company streamlines the hiring process through automated sourcing, AI-driven resume screening, and white-glove contingency services. Their mission is to modernize recruitment by enabling companies to discover and engage passive candidates efficiently, ensuring high-quality hires for critical roles.

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