Ebenezer Gideon Reuben

I’m an analytical, results-oriented Mathematics graduate with hands-on experience in data analysis, machine learning, business intelligence, and technology-driven problem solving. In my Data Scientist Intern role at GWorldSoft Solutions, I prepared and cleaned datasets of over 1,000,000+ records to surface actionable business insights. I also supported operational dashboards and reports that improved team visibility into key business metrics and performance indicators.

I apply statistical methods and machine learning techniques to understand customer behavior, identify trends and patterns, and deliver insights that inform decision-making. Through projects like Credit Loan Default Prediction, Financial Fraud Transaction Detection, and an NLP-based Customer Complaint Classification System, I’ve built predictive and anomaly detection pipelines and improved service efficiency through automated categorization and routing. I’m a fast learner who collaborates well across teams and adapts in dynamic, fast-paced environments—especially where data and digital tools can drive innovation and operational excellence in banking and financial services.