Risk & Actuarial AI Expert

• Bachelor’s or Master’s degree in Actuarial Science, Mathematics, Statistics, Data Science, or a related field
• Progress toward actuarial certification (e.g., IFoA, SOA, or equivalent) preferred
• 2–8 years of experience in actuarial analysis, risk management, or insurance analytics
• Strong expertise in loss ratio and combined ratio analysis
• Proven experience in portfolio risk assessment and risk modeling
• Hands-on experience with catastrophe modeling tools and exposure management frameworks
• Proficiency in programming (Python/R) and data visualization tools
• Familiarity with machine learning techniques and their application in insurance
• Strong problem-solving skills and ability to communicate complex insights to non-technical stakeholders

You will play a central role in evaluating and optimizing portfolio performance through detailed loss ratio and combined ratio analysis. This includes monitoring trends, identifying deviations, and providing recommendations to improve underwriting profitability. A deep understanding of claims behavior, pricing adequacy, and expense structures will be critical to success in this area.

In addition, you will conduct comprehensive portfolio risk assessments, using statistical models and AI-driven techniques to evaluate exposure across various lines of business. This involves identifying risk concentrations, assessing diversification, and supporting strategic decisions related to risk selection and capital allocation. You will collaborate closely with underwriting, finance, and product teams to ensure alignment between risk appetite and business objectives.

A significant part of the role will focus on catastrophe modeling and exposure management. You will work with catastrophe models and geospatial data to assess potential losses from natural disasters and extreme events. Enhancing traditional modeling approaches using machine learning techniques to improve prediction accuracy and scenario analysis will be a key expectation. You will also contribute to stress testing, scenario planning, and regulatory reporting requirements.

The role requires leveraging modern AI/ML techniques to automate actuarial workflows, improve predictive modeling, and uncover hidden patterns in large datasets. You will design and implement models that enhance pricing, reserving, and risk selection processes. Experience with tools such as Python, R, and cloud-based analytics platforms will be valuable.

We value individuals who combine technical rigor with business intuition. You should be comfortable working in a dynamic environment, handling ambiguity, and driving innovation through data. A proactive mindset, attention to detail, and the ability to translate analytical findings into strategic recommendations will set you apart in this role.