Chizurum

• Designed and deployed end-to-end data visualisation dashboards in Tableau and Excel, integrating pivot tables and dynamic charts to deliver real-time KPI visibility to senior stakeholders. • Cleaned, standardised, and pre-processed large-scale datasets using Python (Pandas, NumPy) and SQL, achieving a 95% improvement in data quality and reliability for downstream analysis. • Automated recurring analytics workflows with Python scripting, eliminating 10+ hours of manual reporting per week and improving reproducibility across the team. • Developed and optimised SQL queries and stored procedures, reducing high-volume query execution times by 40% and significantly improving database performance. • Built and prototyped machine learning models (Scikit-learn, TensorFlow) to support business forecasting, improving predictive accuracy for operational decision-making. • Coordinated a cross-functional team of data professionals, improving project delivery efficiency by 20% through structured collaboration and deadline management. • Partnered directly with business stakeholders to define KPIs, ensuring analytical outputs aligned with strategic priorities and informed executive decision-making.

• Completed end-to-end data science projects covering supervised and unsupervised learning, data visualisation, and model evaluation on real-world datasets. • Built classification and regression models using logistic regression, decision trees, and neural networks in Python and SQL, achieving strong predictive performance benchmarks.

• Digitised and structured large volumes of survey data into clean, analysis-ready Excel datasets for the Next Steps Southwest longitudinal research project. • Applied advanced Excel functions (VLOOKUP, pivot tables, conditional formatting) to validate and organise datasets, reducing errors and streamlining reporting workflows.