Remote Capital Modeling Lead, P&C Insurance

CSAA Insurance Group; Clayton (MO); Remote; USD 178,000 - 237,000; Full time

Benefits offered by this job

Remote-first culture

Annual bonus eligibility

401(k) with company match

Flexible workplace

Job summary

CSAA Insurance Group is seeking a Capital Modeling Lead, P&C Insurance, in a remote role open to candidates nationwide in the United States (excluding Hawaii and Alaska). You will lead the development of internal economic capital models and collaborate across risk, investments, product, and FP&A to drive capital decisions.

The ideal candidate has 10+ years of quantitative insurance modeling experience, expert Python/R skills, and a strong understanding of Monte Carlo methods, VaR/TVaR, and

Qualifications

• Bachelor’s degree in a related field or equivalent combination of education and experience.
• 10+ years of related experience in P&C insurance economic capital modeling or enterprise risk modeling.
• Proven ability to design or build stochastic insurance models, not just operate existing ones.
• Strong understanding of Monte Carlo simulation, VaR/TVaR, dependency modeling and risk attribution.
• Experience with catastrophe modeling and reinsurance concepts is preferred.

Responsibilities

• Develop and maintain CSAA IG's internal economic capital models and analytics.
• Collaborate with ERM, Actuarial, Reinsurance, Investments, and FP&A to drive capital decisions.
• Design and implement stochastic capital models integrating underwriting, reserve, catastrophe, credit and investment risks.
• Provide independent technical challenge and governance for capital model results.

Skills

Python

R

Quantitative analysis

Education

Bachelor’s degree in a related field

Tools

ReMetrica

Git

Job description

CSAA Insurance Group is seeking a Capital Modeling Lead, P&C Insurance, in a remote role open to candidates nationwide in the United States (excluding Hawaii and Alaska). You will lead the development of internal economic capital models and collaborate across risk, investments, product, and FP&A to drive capital decisions.

The ideal candidate has 10+ years of quantitative insurance modeling experience, expert Python/R skills, and a strong understanding of Monte Carlo methods, VaR/TVaR, and