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Data Analyst with 1+ years in Statistical Modeling & Data Visualization
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Data Analyst with 2 years of experience leveraging data-driven insights to solve business problems and support strategic decision-making. Skilled in statistical modeling, risk assessment, and data visualization using Python, SQL, Excel, Tableau, and Power BI. Adept at transforming raw datasets into actionable insights that improve operational efficiency, enhance customer experience, and inform risk and underwriting decisions. Strong communicator with proven ability to collaborate across teams and present findings to both technical and non-technical stakeholders.
University of Ibadan
B.Sc. · Computer Science
August 1, 2020 – June 30, 2024
Data Science Nigeria (DSN)
Data Analyst
October 1, 2024 – July 1, 2025
Lagos Island, Lagos State, Nigeria
Octave Analytics and Insights Ltd.
Data Analyst
February 1, 2023 – August 1, 2023
Lagos Island, Lagos State, Nigeria
University College Hospital
Data Analyst Intern
December 1, 2021 – February 1, 2022
Ibadan North, Oyo State, Nigeria
Customer Lifetime Value Prediction
June 1, 2026 – Present
Developed a regression model in SQL and Python to forecast customer lifetime value (CLV) based on policy history and engagement. Insights were used to optimize retention strategies.
Risk Profiling Dashboard
June 1, 2026 – Present
Designed an interactive Power BI dashboard to visualize customer demographics, policy types, and claim frequencies. Improved underwriting decision-making with 20% faster reporting turnaround.
Premium Pricing Optimization
June 1, 2026 – Present
Conducted statistical analysis on historical insurance data to model fair premium pricing, balancing profitability and customer affordability.
Healthcare Claim Trends
June 1, 2026 – Present
Analyzed large claims datasets in SQL to uncover patterns in hospital admissions, claim frequency, and costs, providing insights for fraud monitoring and strategic planning.
Churn Analysis for Policyholders
June 1, 2026 – Present
Applied survival analysis and clustering techniques to identify at-risk insurance customers. Helped design interventions that improved retention campaigns by 15%.
Claims Fraud Detection
June 1, 2026 – Present
Built a classification model in Python using Logistic Regression and Random Forest to identify potentially fraudulent insurance claims. Achieved an F1-score of 87%, reducing false positives and improving risk management.
Cultural Fit Analysis
The candidate's project diversity, including insurance and healthcare domains, shows a broad interest and ability to adapt to different business contexts. Their experience in roles directly aligned with 'Data Analyst' and the breadth of skills (ML, visualization, statistical analysis) indicate a strong cultural fit for a data-driven organization. The academic achievements further highlight a commitment to excellence.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving and communication skills through project descriptions and professional summary. Their experience in A/B testing and stakeholder engagement suggests a collaborative work attitude. The diverse project portfolio indicates adaptability and a proactive approach to learning and applying new techniques.