Data Analyst with less than a year in Actuarial Science & Financial Modelling
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Assessing your cultural and operational fit
Analytical and detail-driven Actuarial Science graduate with strong grounding in financial mathematics, risk modelling, life contingencies, and statistical analysis. Skilled in R, Python, SQL, and Excel-based actuarial modelling, premium pricing and survival analysis, with hands-on experience in building analytical models, cleaning datasets, and presenting insights clearly. Currently pursuing IFoA exams and seeking an entry-level actuarial analyst role within insurance or consulting.
University of Zambia
BSc · Actuarial Science
January 1, 2022 – January 1, 2025
MPOPOMA HIGH SCHOOL
A'-Level (ZIMSEC)
January 1, 2018 – January 1, 2019
Turn Up Group Of Companies
Risk Analyst
December 1, 2025 – Present
India
Life Insurance Premium Calculation Tool (Excel & R)
June 1, 2026 – Present
Developed a simplified model to calculate net premiums using mortality tables, interest assumptions, and life contingencies principles.
Survival Model Estimation (R Project)
June 1, 2026 – Present
Built a basic survival analysis model to estimate expected lifetimes using student-generated data, applying Kaplan-Meier methods and comparing model outputs.
Claims Frequency Modelling (Python)
June 1, 2026 – Present
Created a Poisson-based model to simulate claim events and estimate expected claim frequencies for a hypothetical insurer.
IFoA Actuarial Exams (In Progress)
IFoA
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic background in Actuarial Science and pursuit of IFoA exams demonstrate a strong interest and commitment to a data-driven, analytical field. The projects, though academic, show initiative in applying theoretical knowledge. The 'Risk Analyst' role, even if entry-level, indicates exposure to business operations and risk management, which can be valuable for understanding data context. The listed interests like 'Actuarial research', 'Insurance markets', and 'Data storytelling' further suggest alignment with a culture that values continuous learning, industry knowledge, and effective communication of insights.
Soft Skills & Operational Fit
The candidate's resume highlights analytical thinking, problem-solving, statistical modeling, communication, risk fundamentals, attention to detail, and adaptability as key strengths. These align well with the demands of a Data Analyst role, particularly in an environment requiring rigorous data interpretation and clear reporting. The experience in streamlining administrative processes also suggests an operational efficiency mindset.