• We are seeking experienced Actuarial Professionals to support the development and training of advanced Artificial Intelligence systems.
• In this role, you will create, evaluate, and refine realistic actuarial scenarios involving risk assessment, pricing, reserving, forecasting, profitability analysis, and financial modelling.
• Leveraging your actuarial expertise, you will ensure AI-generated outputs are technically accurate, methodologically sound, and aligned with professional actuarial standards and real-world insurance and financial services practices.

Key Responsibilities

• Develop high‑quality actuarial tasks, scenarios, and model solutions that meet the expert quality standards across pricing, reserving, risk modeling, and valuation domains.
• Evaluate and refine AI‑generated actuarial outputs under senior review, incorporating calibration feedback to improve technical accuracy, consistency, and reasoning.
• Apply rubric criteria established by the Functional SME Lead to ensure all work aligns with professional actuarial methodologies, regulatory expectations, and industry best practices.
• Validate the soundness of assumptions, calculations, and modeling logic to ensure outputs reflect real‑world actuarial practice and defensible analytical judgment.
• Iterate on task design, evaluation methods, and solution frameworks to continuously enhance AI performance across actuarial analysis, forecasting, and risk assessment workflows.

Requirements

• Education: Bachelor's Degree or equivalent practical experience in Actuarial Science, Mathematics, Statistics, Finance, Economics, or a related quantitative discipline.
• Professional Experience: Minimum of 3 years of professional actuarial experience with demonstrated experience in: Actuarial Reserving, Pricing, Risk Assessment, Forecasting, Financial Modelling, Profitability Analysis
• Professional Qualifications: Recognized actuarial qualification with multiple examinations completed through any of these institutes: Society of Actuaries (SOA), Casualty Actuarial Society (CAS), or Institute and Faculty of Actuaries (IFoA)
• Preferred Qualifications:
  • Experience in AI evaluation, data annotation, content review, or quality assurance is an advantage but not required.
  • Strong understanding of insurance products, actuarial methodologies, and financial risk management.
  • Ability to communicate complex actuarial concepts in a clear and structured manner.
  • Experience developing or reviewing actuarial reports, pricing models, or reserve analyses.