Benjamin Ilevbare

I’m a results-driven Data Scientist focused on turning complex data into measurable business value. I blend exploratory data analysis, predictive modeling, and data visualization to help stakeholders make faster, smarter decisions.

In my work, I’ve built and evaluated models for customer segmentation and churn-risk analysis, including K-Means–based solutions with cluster validation using the Elbow Method and Silhouette Analysis. I also translate model outputs into practical actions—such as targeted marketing strategies and retention recommendations.

My technical approach is hands-on and end-to-end: I develop regression pipelines, perform preprocessing (imputation, encoding), and communicate results through clear, non-technical visual storytelling. I’ve demonstrated strong performance in predictive tasks, including an Auto MPG regression model with R² of 0.86.

I’m currently expanding my expertise with cloud-based data platforms and deep learning to deliver more scalable, real-world AI solutions. I also bring a strong operational and support mindset from IT experience, which strengthens how I document, report, and drive continuous improvement.