Results-driven Data Science/Machine Learning Engineer with expertise in data analysis, machine learning, predictive analytics, deep learning, NLP, computer vision, and AI, delivering end-to-end solutions from design to deployment. Proficient in transforming complex data into scalable, production-ready applications and visualization, leveraging Python, TensorFlow, PyTorch, SQL, PowerBI, and Microsoft Azure. Recognized for translating complex insights into actionable strategies and driving measurable business value across diverse domains including education, healthcare, finance, and business intelligence. Holds a master's degree in data and information science
Phone: +234 706 789 2597
Email: ijeomaegbeke@gmail.com (Primary)
Alternative: giftegbeke@gmail.com
LinkedIn: http://www.linkedin.com/in/ijeomaegbeke
Examinations & Records Officer
Ibadan, Nigeria
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Summary
Managed examination administration and academic records in a structured educational environment, ensuring strict compliance with examination regulations, confidentiality, and institutional standards. Responsible for preparing and securely handling examination materials, coordinating examination schedules and logistics, supporting supervision during examinations, and accurately collating and maintaining student results and records. Consistently ensured accuracy, integrity, and proper documentation in all examination-related processes.
Highlights
Managed and maintained large volumes of student records with strict data standards, ensuring high accuracy and confidentiality
Processed and validated examination data, including result collation, verification, and updates across records
Prepared structured reports and performance summaries for administrative decision-making
Reviewed submitted examination data/records for completeness, correcting errors and flagging inconsistencies
Maintained organized documentation and logs of updates, corrections, and record changes
Managed typing and data entry of examination question papers and administrative records with a high level of accuracy and confidentiality.
DATA SCIENTIST INTERN
Nigeria
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Highlights
Collected, cleaned, and prepared large datasets, significantly improving model accuracy and analysis speed by 15%.
Designed, trained, and deployed machine learning models, achieving 85–95% prediction accuracy for key business challenges.
Conducted statistical analysis and developed interactive visualizations, enhancing decision-making efficiency for stakeholders.
Built and maintained automated data pipelines, dashboards, and reporting tools, reducing manual reporting effort by 30%.
BUSINESS EXECUTIVE AND ANALYST
Kansas City, Missouri, US
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Summary
Drove business growth and operational efficiency through strategic analysis, client relationship management, and data-driven reporting.
Highlights
Designed interactive Power BI dashboards and SQL models to effectively track sales KPIs and inform strategic decisions.
Conducted comprehensive market and competitor analysis, shaping strategies that increased service adoption by 15%.
Applied customer analytics to develop targeted engagement strategies, significantly improving customer retention.
Built and maintained strong client relationships, generating repeat business and securing over 20 referrals.
Delivered concise sales and financial reports, guiding leadership on key revenue growth opportunities.
Msc
Data and Information Science
Courses
Python
SPSS
Database Management System
Information Retrieval
Technical Writing
Qualitative and Quantitative Analysis
Information Technologies
Information System Analysis
Project Management
Microsoft Office Packages
Bsc
Home Science and Management
Python, MySQL, Data Modeling & Design, Data Structures, Data Governance, SQL.
Supervised Learning, Unsupervised Learning, Reinforcement Learning, Model Evaluation, Model Optimization, Scikit-learn, Logistic Regression.
Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), TensorFlow, PyTorch.
Text Classification, Sentiment Analysis, Transformers (Hugging Face), Tokenization, Stopword Removal, Vectorization, CountVectorizer.
Image Classification, Object Detection, Feature Extraction, Face Recognition, OpenCV, dlib.
TensorFlow, PyTorch, Scikit-learn, Jupyterlab, Visual Studio Code, Google Colab, FastAPI, Gradio, CMake.
Matplotlib, Seaborn, Power BI, Microsoft Fabric, Data Preprocessing & Cleaning, DAX, Data Modeling, WordCloud.
Microsoft Azure, Render, API Development, Model Optimization, Deployment & Monitoring.
Microsoft Word, Excel, PowerPoint, Access, Slack.
Analytical Thinking, Scalable AI Solutions, Efficient AI Solutions, Production-Ready AI Solutions.
Cross-functional Teamwork, Stakeholder Engagement, Technical Results Translation, Business Value Communication.
Self-Motivation, Resilience, AI/ML Technologies.
Summary
Designed a machine learning-based predictive system to forecast customer churn for e-commerce businesses, enabling proactive retention strategies and improving long-term customer loyalty. Technologies: Python, Scikit-learn, Pandas, NumPy, Matplotlib/Seaborn, Google Colab, Gradio
Summary
Conducted a geospatial analysis of health facilities across Nigeria, focusing on the spatial distribution and accessibility within Local Government Areas (LGAs), with a detailed subset analysis of Oyo State. Technologies: Python, GeoPandas, Folium, Shapely, Rasterio, Pandas, Matplotlib
Summary
Created a word cloud to highlight frequently mentioned terms in customer reviews, enabling businesses to quickly identify positive remarks of customers, supporting marketing, customer engagement, and data-driven decision-making. Technologies: Python, Pandas, Matplotlib, WordCloud
Summary
Built a natural language processing sentiment analysis application that automatically classifies customer reviews as positive, negative, or neutral, enabling businesses to quickly gauge customer satisfaction and make data-driven improvements. Technologies: Python, Scikit-learn, Tokenization, CountVectorizer, Pandas, NumPy, Google Colab, Gradio
Summary
Developed an AI-powered face recognition system that automates attendance logging using live webcam detection, enhancing reliability and accountability by eliminating manual check-ins and loopholes in traditional methods. Technologies: Python, OpenCV, dlib, face_recognition, Gradio, CSV (data handling), CMake (build dependency)
Summary
Developed a predictive machine learning system to estimate the likelihood of loan default, enabling financial institutions to make data-driven, risk-aware lending decisions, improving financial stability and profitability. Technologies: Python, Scikit-learn, Logistic Regression, Pandas, NumPy, Matplotlib, Google Colab, Gradio
