I'm a 1st class BSc Computer Science graduate with a keen interest in full-stack development & machine learning.

Seeking 2026 graduate software roles or placements nationwide.

Languages: C#, Python, Java, HTML & CSS, SQL (MySQL & SQL Server)

Web Frameworks: Angular, ASP.NET

Data & Machine Learning: Pandas, Matplotlib, Numpy, Sci-kit Learn, supervised learning, exploratory analysis and preprocessing

Architecures & Practices: Clean Architecture, Command Query Responsibility Segregation (CQRS), Agile development, Unit/Integration/E2E testing

Tools: Git, RabbitMQ, Docker, JWT authentication

I'm actively expanding my technical portfolio and commercial experience through personal and industry projects across data analysis, machine learning, and full-stack web development.

My current personal projects allow me to maintain my software development proficiency and help build my technical knowledge across maintainability, scalability, DevOps practices, and cloud deployment. I am particularly interested in projects that combine data analytics and management with web development, allowing me to build more practical, robust, and deployable software solutions.

Gaining industry experience is also really important to me, I have completed a placement with HARTS (Hospital Arts, Liverpool) as a Junior Business Systems Developer. I developed a database management desktop application during this time to reduce the administrative workload for members of staff.

I am currently working for VuelaNova as a full-stack engineer, tasked with the end-to-end development of their website with regular stakeholder engagement, contributing towards an Agile team.

Bartering Platform: A full-stack .NET 8 microservices and Angular frontend application with a strong focus on modularity and loose coupling. The application serves as a platform for exchanging goods/products between users based on selected filters, showcasing architectural patterns such as CQRS and Clean Architecture, RabbitMQ messaging. Please refer to my Bartering-Platform repository for further details.

Hospitality Sales Forecasting Platform (Currenly on hold): A capstone web application, .NET backend and Angular frontend, following Clean Architecture whilst leveraging machine learning (approach established from comparative forecasting experiments in another project)to accurately forecast hospitality sales. The goal is to improve staffing and inventory decisions. Please refer to my Hospitality-Sales-Forecasting-Platform repository for further details.

Comparative evaluation of forecasting approaches for hospitality sales: Implementation and comparative evaluation of forecasting hospitality sales using SARIMAX, XGBoost, and Lasso. Models trained on cleaned & preprocessed data, using identical expanding-window time-aware evaluation protocols, with appropriate MAE, RMSE, and MASE metrics reported and compared alongside forecasting behaviour and redisudal diagnostics. Additional analyses include imputation strategy analysis, training optimisation analysis, and feature-contribution analysis. Please refer to my Comparative-Forecasting-Analysis repository for further details.

Student Planner: Python & Tkinter project centred around turning a student's day into a focused checklist, syncing tasks & assignments with the user's Google Calendar. Tasks can be added, modified, deleted, categorised (module specific or general) and checked off through a simple, navigable interface featuring a prominent day-to-day checklist. Please refer to my Student-Planner repository for further details.

Database Management System: Built during my Junior Business Systems Developer role at Hospital Arts (HARTS), Liverpool: Python & Tkinter desktop application centralising admin data, reducing the manual workload for members of staff. Please refer to my Database-Management-System repository for further details.