Agyekum: The Analytics Engineer
I build practical analytics, workflow automation, and Machine Learning (ML) solutions in Python that improve operational efficiency and decision-making. This portfolio features an end-to-end Player Performance ML Pipeline, a Pharmacy Inventory & Revenue Analytics System, and an automated staff onboarding/ID generation workflow for a regulated healthcare environment. I focus on clean data workflows, explainable insights, and reliable reporting that supports real-world decisions.
Featured Projects
High-impact builds across multi-sport analytics, operational systems, and workflow automation.
Player Performance ML Pipeline (Multi-Sport)
End-to-end predictive modelling pipeline using KPI engineering, PCA, evaluation metrics, and SHAP explainability.
Pharmacy Stock Management System
Inventory and stock tracking system designed to improve accuracy, reduce stock-outs, and support daily operations.
Care Staff ID Automation (Anonymised)
Automated staff onboarding and ID generation workflow built for a regulated care environment-reducing admin time and improving consistency.
More Projects
Web, business intelligence, and sector-focused systems supporting revenue and service delivery.
Rich Comfort Hotel - Revenue & Booking Analytics
Hospitality analytics and booking workflow improvements focused on occupancy, pricing, and revenue reconciliation.
Nagma Enfield - Recruitment Intelligence Platform
Recruitment analytics platform supporting sourcing, placement tracking, and GDPR-aligned applicant data handling.
CV - Samuel Agyekum
Download my CV for a full overview of education, awards, and professional projects.
Skills Snapshot
Data Analytics & IT Security - Building practical Python ML pipelines and decision-ready insights.
ML: Logistic Regression, Random Forest, PCA, SHAP • Analytics: Data cleaning, EDA, KPI engineering •
Tools: Python, Tableau, Jupyter, Git/GitHub • Governance: GDPR-aligned data handling, access controls, documentation.