Portfolio
A collection of practical projects and ideas designed to strengthen my analytical skills and solve real problems.
Featured Project
Exploring feedback from churned customers using NLP techniques, sentiment analysis, and Tableau to identify recurring themes and better understand potential drivers of customer churn.
Built using anonymised findings from a previous capstone project.
I'm focusing on projects that reflect the type of problems I enjoy solving: understanding behaviour, improving clarity, and making information easier to use.
Building a single source of truth by combining multiple synthetic datasets into a consolidated reporting dataset.
Current focus:
Data quality, validation checks, duplicate detection, documentation, and creating repeatable reporting processes.
Exploring customer retention patterns and identifying factors that may contribute to churn.
Current focus:
Exploratory analysis, customer segmentation, visualisation, and identifying potential indicators of churn.
Designing a dashboard to communicate revenue performance and key metrics clearly.
Current focus:
KPI tracking, trend analysis, visual design, and communicating insights clearly.
Building confidence with pandas and creating reusable analysis workflows.
Learning how to use AI to support my everyday workflow and automate the repetitive bits — without sacrificing accuracy or human judgement.
Understanding how data, operations, and people interact across teams.
Combining my favourite animal with real-world datasets to explore trends, species information, and conservation insights through data visualisation.
Part of the challenge will be sourcing suitable real-world data to support the analysis.
Exploring anomaly detection techniques and risk indicators to identify potentially suspicious financial transactions.
Investigating how AI can help automate repetitive tasks and improve efficiency while keeping people and context firmly in the loop.