Actuarial Assistant

Location

Contract Type

Knowledge & Work Experience

Understanding of general insurance principles and familiarity with statistical modelling, data analysis, and quantitative problem-solving techniques.
Awareness of the regulatory and business environment within the insurance industry.
Prior actuarial or insurance industry experience is desirable but not mandatory.
Internship, industrial attachment, academic projects, or practical experience involving data analysis, statistical modelling, or insurance related work will be an added advantage.

Academic and Professional Qualifications required

Bachelor’s degree in Actuarial Science, Statistics, Mathematics, Data Science, or a related quantitative field.
Progress towards a recognized actuarial qualification (SOA, IFoA, CAS, or equivalent), with at least one actuarial examination passed being an added advantage.
Demonstrated proficiency in quantitative analysis and use of analytical software tools.

Support the preparation of actuarial analyses relating to pricing, reserving, portfolio performance, and profitability.
Assist in the development, maintenance, and enhancement of actuarial models and analytical tools.
Perform data extraction, validation, and analysis to support actuarial investigations and business decision-making.
Support pricing reviews and contribute to the assessment of rate adequacy across business lines.
Assist in monitoring portfolio experience and identifying company and industry trends in claims, premiums, expenses, and other key performance indicators.
Contribute to the development of new products and enhancement of existing products.
Prepare actuarial reports, management information, and regulatory submissions as required.
Collaborate with underwriting, finance, operations, and other business units to provide actuarial insights and support.
Ensure actuarial work complies with applicable regulatory requirements, professional standards, and company policies.
Participate in initiatives aimed at improving actuarial processes, data quality, automation, and reporting efficiency

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