~/whoami
Machine learning engineer focused on building clear, reliable, and human‑centred solutions — from model pipelines to full end‑to‑end deployments.
~/about
I'm a data scientist and machine learning engineer with a practical, systems‑driven approach to solving problems. I care about clarity — in data, in code, and in communication — and I enjoy taking complex, ambiguous challenges and turning them into structured, working solutions. My work spans model development, evaluation, deployment, and the engineering foundations that make ML sustainable in real environments.
I'm currently building my own portfolio of ML projects while developing a personal website hosted through GitHub and Azure Static Web Apps. I'm also exploring computer vision, especially image classification, and refining a clean, minimalist design aesthetic for presenting technical work.
Get in touch →~/projects
A few projects that best represent how I think and build.
A computer vision project exploring species classification using a curated dataset of tree images. Focused on data cleaning, model experimentation, and building a reproducible training pipeline.
A minimalist, data-scientist-focused personal website built with GitHub, VS Code, and Azure Static Web Apps. Includes automated deployment, a clean project structure, and a design that prioritises clarity and simplicity.
An applied ML project using attendance and engagement data to identify ESOL learners at risk of withdrawing from their course. Built on MS Fabric for data ingestion and training, Power Apps for frontline interaction, and Power BI for actionable reporting — aimed at early intervention.
~/skills
~/contact
Have a project, role, or idea in mind? Send a note — I read every message.