Projects

Built an end-to-end churn modelling workflow to help subscription-style businesses understand and predict which customers are likely to leave, using a Telco-style dataset.

• Cleaned and preprocessed 7,000+ customer records, handling missing values, encoding categorical fields and scaling numerical features.
• Performed EDA to uncover relationships between tenure, contract types, billing patterns and churn behaviour.
• Improved model performance from a baseline of ~70% to ~82% through feature engineering, tuning and cross-validation, with a focus on business-relevant metrics.

Designed a command-line–driven ETL engine to automate payroll data workflows, integrating CSV and SQL sources into a single, reproducible pipeline.

• Implemented a structured flow covering extract → DDL creation → transform → load, reducing manual preparation time from hours to minutes.
• Built repeatable, auditable runs with a scripted pipeline design (configurable and reproducible).

How I approach projects

• Start from a clear business question and success metric.
• Use targeted EDA to shape the data model and feature set, not just generate charts.
• Keep clean, modular notebooks or scripts with clear stages.
• Focus on evaluation that reflects business impact, not just a single score.
• Document assumptions, limitations and next steps for future iterations or deployment.

I build interactive Tableau dashboards that combine clear KPIs, drill-down exploration, and a short “so what” insight layer. Recent work includes a Victoria Road Crash analytics dashboard (real government open data) and a Global Graduate Employability dashboard (synthetic dataset for demonstration).