Actuarial Analytics
New York, NY
Responsibilities Work with potential clients to gather historical performance data and develop loss forecasts using proprietary stochastic models in support of structuring, pricing, and placing reinsurance transactions in the casualty ILS and collateralized reinsurance markets. Build production-grade analytical tools and modeling infrastructure, working closely with software engineers and data scientists. Develop and maintain scalable, well-tested modeling code using modern software engineering practices. Use AI-assisted development tools and modern data workflows to accelerate model development, testing, and deployment. Lead the design and implementation of new analytical capabilities from concept through production. Translate actuarial and statistical insights into clear written and verbal communication for technical and non-technical stakeholders. Contribute to architectural decisions around actuarial modeling platforms and data pipelines.
Requirements ACAS required; FCAS strongly preferred. 7+ years of actuarial experience in casualty (re)insurance. Bachelor’s or Master’s degree in a relevant quantitative field. Demonstrated experience developing actuarial or statistical models used in real-world decision-making. Strong programming skills in Python, including experience building reusable analytical tools. Familiarity with modern software development practices (version control, testing, code review).
Preferred Experience Experience with insurance portfolio modeling, stochastic simulation, or capital modeling. Experience using AI-assisted development tools or machine-learning workflows. Experience deploying models into production environments. Experience working in a fast-moving, product-oriented technical environment. Experience working in cross-functional technical teams including software engineers and/or data scientists. Experience building analytical tools or internal software platforms is strongly preferred.