Job Overview
We are seeking a mathematically-inclined and analytical Training Support Specialist in Risk Analysis & Premium Calculation to join our team. As the insurance and financial markets become increasingly data-driven, your role is to provide essential support to training programs focused on actuarial science and risk management. You will facilitate the delivery of curricula that blend statistical modeling, financial theory, and regulatory compliance, ensuring that learners are equipped to assess risk accurately and price insurance products effectively.

Job Responsibilities
Program Coordination: Manage the logistical execution of specialized training modules, ensuring that actuarial software, data sets, and instructional materials are optimized for professional development.

Instructional Support: Assist Lead Instructors in facilitating workshops on key topics, including probability theory, loss modeling, experience rating, and the mechanics of premium determination.

Applied Lab Facilitation: Support practical sessions where learners use industry-standard software (e.g., R, Python, or actuarial modeling tools) to perform stochastic simulations, calculate pure premiums, and apply loading factors.

Curriculum Maintenance: Assist in keeping training content updated regarding the latest actuarial standards, shifts in mortality/morbidity tables, and evolving regulatory requirements (e.g., Solvency II, IFRS 17).

Assessment & Performance Tracking: Coordinate the evaluation of complex quantitative assignments and capstone modeling projects. Provide supplemental guidance on mathematical concepts and data-cleaning techniques.

Industry & Stakeholder Liaison: Organize guest lectures with professional actuaries and risk consultants. Facilitate networking events that connect learners with industry leaders in insurance and financial risk management.

Quality Assurance: Monitor the effectiveness of quantitative training by analyzing learner progress and providing insights to the program management team for continuous improvement.

Job Requirements
Education: Bachelor’s degree in Actuarial Science, Mathematics, Statistics, Finance, or a related field (progress toward an actuarial qualification—SOA/CAS/IFoA—is highly preferred).

Experience: 1–3 years of professional experience in insurance, risk analysis, or quantitative modeling, combined with an interest in educational support.

Technical Skills:

Strong proficiency in Excel and statistical software (e.g., R, Python, SAS).

Understanding of insurance mathematics, risk theory, and financial forecasting.

Familiarity with database management and data visualization tools.

Soft Skills:

Quantitative Rigor: Ability to maintain precision in high-stakes mathematical calculations.

Analytical Communication: Ability to explain complex statistical models to non-actuarial audiences in a clear, professional manner.

Detail-Oriented: Exceptional organizational skills to manage large data sets and technical lab schedules.

Integrity: A commitment to the ethical standards of professional risk reporting and financial management.

Benefits
Competitive Compensation: Attractive salary package with potential for performance-based bonuses tied to program success.

Professional Development: Support for ongoing actuarial exams, attendance at major insurance/risk conferences, and access to internal technical workshops.

Collaborative Environment: Access to an interdisciplinary team of subject matter experts in insurance, economics, and data science.

Comprehensive Benefits: Full health insurance, paid leave, and retirement benefits in accordance with local labor laws.

Career Growth: Defined pathways toward roles such as Actuarial Analyst, Risk Manager, Quantitative Modeler, or Program Lead.

Actuarial Training Coordinator, Risk Analysis Support Specialist, Premium Calculation Assistant, Quantitative Finance Associate, Academic Support (Actuarial Science).

Industry Keywords: Actuarial Science, Risk Analysis, Premium Calculation, Stochastic Modeling, Loss Modeling, Financial Risk, Insurance, Data Analytics.

Attributes: Mathematical, Analytical, Methodical, Precision-focused, Strategic, Communicative.

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