Simbarashe Moyana

I am an Actuarial Science honours graduate with substantial progress toward professional qualification, having completed 8 of 13 ASSA examinations and obtained multiple university exemptions. My academic focus centers on banking and life insurance, with exposure to general insurance and actuarial risk management.

During my honours research I investigated the efficacy and adoption of machine learning in asset–liability modelling, conducting semi-structured interviews across short-term and long-term insurers to evaluate processes and benefits. This work sharpened my analytical and research skills and reinforced my interest in data-driven actuarial solutions.

I have practical teaching experience as a university teaching assistant for first-year Financial Mathematics and Demography, supporting students in core actuarial concepts and problem-solving. I also participated in a virtual actuarial development program that translated classroom theory into real-world applications.

I bring strong programming skills in R and Python, solid communication and teamwork abilities, and a methodical, detail-oriented approach to problem solving. I am motivated to apply my actuarial knowledge within insurance or banking environments where I can contribute to modelling, pricing, and risk management initiatives.