Closer to client-facing consulting than an internal modelling role—the work is judged by executive decisions and engagement delivery, not just model production.
Titled below the requirements. The posting title says Manager II, while the description presents a Vice President role with technical review ownership, engagement management, executive exposure, and analyst development.
Vice President-level P&C risk analytics and actuarial consulting role in New York, focused on peer review, stochastic modeling, risk financing, and client engagements. You’ll oversee analytical quality, guide analysts, and present uncertainty and financial trade-offs to CFOs, Treasurers, and other executives. The role is hybrid, with at least three days per week in a local office or at client sites.
Requirements
Must have
Six or more years of relevant technical experience in actuarial analysis, statistics, mathematical modeling, data science, risk analytics, or a related quantitative field
Strong foundation in probability, statistics, and quantitative modeling with judgment to evaluate assumptions and recognize model limitations
Experience reviewing complex analytical work, identifying errors or inconsistencies, and providing actionable feedback
Strong project management skills including coordinating contributors, managing competing priorities, and delivering on deadlines
Clear written and verbal communication skills to explain technical concepts and business implications to nontechnical audiences
Collaborative approach to problem-solving, accountability for work quality, and interest in coaching and developing colleagues
Strongly preferred
Actuarial exam progress toward ACAS or FCAS, or earned ACAS or FCAS designation
Other actuarial credentials, including ASA or FSA
Insurance experience in property and casualty, loss modeling, insurance program evaluation, or risk financing
Consulting or advisory background with experience managing client engagements and translating analysis into practical business guidance
Experience with stochastic modeling, Monte Carlo simulation, predictive modeling, or retained-loss analysis
Experience presenting analytical findings to senior executives and responding confidently to questions about assumptions, results, and uncertainty
