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Data Analyst with 2+ years in statistical analysis and visualization.
Monitoring, Evaluation and Data Analytics professional with strong expertise in statistical analysis, data management, and evidence-based decision support. Experienced in analysing large datasets, building dashboards, and supporting programme monitoring through structured data systems and survey-based research. Proficient in Python, SQL, Excel, and Power BI for data analysis and visualization. Adept at translating complex data into clear insights that support programme improvement, operational efficiency, and informed decision-making.
Nexford University
Master's of Science · Data Analytics
August 1, 2024 – June 30, 2025
Federal University of Technology, Minna
Bachelor of Technology · Mathematics(Statistics)
August 1, 2016 – June 30, 2023
Setraco Nigeria Limited
Assitant Cost Control Officer
November 1, 2025 – Present
Abuja, Federal Capital Territory, Nigeria
Inspiresia Technologies Limited
Project Analyst
March 1, 2025 – July 1, 2025
Abuja, Federal Capital Territory, Nigeria
The Sparks Foundation
Data Science & Business Analytics(Remote)
August 1, 2024 – August 1, 2024
Abuja, Federal Capital Territory, Nigeria
Terra Learning(Internship)
Data Analytics with Power BI(Remote)
July 1, 2024 – August 1, 2024
Abuja, Federal Capital Territory, Nigeria
Dotmac Technologies Limited
Data Analyst
October 1, 2023 – July 1, 2024
Abuja, Federal Capital Territory, Nigeria
Digi-Realm City Solutions
Data Analyst
April 1, 2021 – September 1, 2021
Bosso, Niger State, Nigeria
Cancer Diagnosis using Artificial Neural Networks (ANNs)
August 27, 2025 – August 30, 2025
This project was developed as part of a data analytics assignment to explore the use of Artificial Neural Networks (ANNs) in classifying cancer cases (Malignant vs Benign) using the Breast Cancer dataset from the MD Anderson Cancer Institute. The workflow covers dataset exploration, preprocessing, ANN modeling, evaluation, and insights.
View ProjectBreast Cancer PCA Analysis
May 24, 2025 – May 26, 2025
This project demonstrates the application of Principal Component Analysis (PCA) to the Breast Cancer dataset from sklearn.datasets. The goal is to reduce the dimensionality of the dataset and identify essential variables for donor funding strategies, as assigned by the Anderson Cancer Center. Logistic regression is applied as an optional bonus for predictive modeling.
View ProjectPython for Beginners
Simplilearn
June 1, 2026 – Present
Foundations of Business Analytics
Nexford University
June 1, 2026 – Present
Python Quick Start
Linkedin Learning
June 1, 2026 – Present
Accounting and Financial Reporting
Nexford University
June 1, 2026 – Present
Power BI for Beginners
Simplilearn
June 1, 2026 – Present
Data Science and Analytics
HP Life
June 1, 2026 – Present
Business Analysis Foundations
Linkedin Learning
June 1, 2026 – Present
A Day In The Life of a Data Scientist
Linkedin Learning
June 1, 2026 – Present
Data Analysis
Digi-Realm City Solutions
June 1, 2026 – Present
Data Analytics
Terra Learning
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project experience, ranging from cost control in construction to digital literacy surveys and sales analysis, indicates adaptability and a broad interest in applying data analytics across different domains. Their involvement in extracurricular leadership roles suggests a proactive and collaborative mindset. The pursuit of a Master's in Data Analytics while gaining practical experience shows a commitment to continuous learning and professional growth, aligning well with a culture of innovation and development.
Soft Skills & Operational Fit
The candidate demonstrates strong organizational skills through documentation management and record-keeping. Their experience in coordinating and verifying requests, as well as supporting internal controls, suggests a detail-oriented and responsible work attitude. The ability to present insights and collaborate with stakeholders indicates good communication and teamwork potential. The extracurricular activities also highlight leadership and accountability.