I’m a Data Scientist with 5+ years of cross-functional experience spanning healthcare, finance, and business operations. Skilled in Python, R, SQL, and Power BI, I specialize in developing machine learning models, building interactive dashboards, and translating complex data into strategic business insights.
I’m particularly passionate about:
Professional qualifications that validate my expertise
Issued by WorldQuant University
started Oct 2025
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Issued by WorldQuant University
In Progress
Issued by Udemy
July 2025
Issued by Udemy
October 2025
Developed an Intelligent Media Recommendation System leveraging LangChain, Llama 3, and Groq to generate personalized content suggestions from multimodal data sources. Optimized retrieval pipelines, embedding generation, and prompt engineering for context-aware recommendations in real time, achieving scalable and production-ready deployment.
Developed AutoPrice-AI, an intelligent car valuation system leveraging machine learning and regression modeling to uncover key price-driving factors. Achieved high predictive accuracy through automated feature engineering, hyperparameter tuning, and EDA-driven model optimization using Scikit-learn and XGBoost for production deployment.
Analyzed U.S. college data to explore the relationship between economic diversity and student outcomes. Conducted extensive data cleaning, visualization, and regression modeling to identify socioeconomic patterns influencing graduation rates, mobility, and institutional performance using Pandas, Seaborn, and Scikit-learn.
Performed comprehensive data preparation and cleaning on Cyclistic bike-share datasets to enable accurate usage pattern analysis. Implemented data wrangling, feature standardization, and missing value handling using Python and Pandas, ensuring data integrity for subsequent exploratory analysis and visualization.
Developed a rainfall prediction model using Tidymodels in R, leveraging ensemble stacking to enhance forecasting accuracy. Integrated multiple base learners, optimized hyperparameters, and performed feature selection for robust performance across diverse weather datasets. Delivered interpretable and production-ready insights through model explainability tools.
Conducted exploratory data analysis on U.S. motor vehicle collision datasets to uncover trends, risk factors, and spatial crash patterns. Utilized Python-based visualization and geospatial tools to analyze injury severity, contributing factors, and temporal distributions for data-driven road safety insights.
Built a Power BI dashboard to track key financial KPIs, monitor revenue trends, and analyze profitability across products and regions. Enabled stakeholders to assess YoY growth, margin performance, and customer profitability for informed strategic decision-making.
Designed an interactive Power BI dashboard to visualize revenue performance and customer acquisition trends. Tracked monthly growth rates, top-performing regions, and retention metrics, enabling data-driven insights into sales expansion and customer lifecycle management.
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abayomiajiboye46111@gmail.com
+234 8098-507-180
