Jeremiah Oyewole

I’m a detail-oriented, results-driven Data Analyst focused on collecting, cleaning, and analyzing complex datasets to uncover trends and support strategic decision-making. Through six end-to-end portfolio projects, I deliver data-driven recommendations with measurable business impact, especially in A/B testing, predictive modelling, business intelligence, and statistical analysis.

In my SQL work, I built end-to-end Microsoft SQL Server analytics (including CTEs, window functions, stored procedures, and views) to explain what separates high- and low-performing stores, enabling clearer quarterly tracking. I’ve run rigorous experiments with statistical testing (including a two-tailed Z-test and power analysis), and I’ve built predictive models such as churn prediction where XGBoost reached 89.24% accuracy and AUC-ROC of 0.9557. I also deploy decision-support dashboards and tools (including Power BI and Streamlit) to make insights actionable for stakeholders.

I value accuracy, structured thinking, and ownership—especially in fast-paced, remote environments. I’m continuing to strengthen my quantitative research and commercial analytics approach through virtual simulations, so I can turn data into evidence-based decisions your team can trust.