I build data-driven and security-aware analytics systems focused on machine learning, explainability, and reproducible delivery.
My work spans sports performance analytics (football + cross-sport testing) and information security / governance in regulated environments.
- Predictive modelling (Logistic Regression, Random Forest) with PCA and robust evaluation
- Model explainability using SHAP (global + individual explanations)
- Translating analytics into decision-ready outputs (clear visuals, documented assumptions, reproducible runs)
- Security + governance in data projects (GDPR-aware processing, risk thinking, auditability)
- Player Performance Analysis in Sports Using Data Analytics
- Information Security Strategy & IT Security Management
- IS Governance Case Study (Regulated UK environment)
See: evidence-index - curated links to key outputs, figures, and supporting explanations.
Python (pandas, scikit-learn, SHAP), Jupyter, Tableau, Jamovi, Git/GitHub
