Hi, I'm Ebenezer Obi
Creating technology solutions that deliver results and solve real-world problems.
Creating technology solutions that deliver results and solve real-world problems.
Computer science student building software that solves real problems for real users. I’ve worked across full-stack development,
data analytics, and production deployment, taking projects from concept to shipped systems. I combine technical depth with
operational understanding: I know how technology supports real-world processes, what breaks under pressure, and how to design for reliability.
I’ve debugged production issues, iterated based on user feedback, and prioritised maintainable, well-documented code. Currently seeking
graduate roles, open to relocation, where I can apply strong technical execution, operational awareness, and a bias toward shipping meaningful solutions.
BSc (Hons) Computer Science
University of Chester
Expected Graduation: 2026
A cloud-based temporary file-sharing app — securely upload files, set passwords and expiration times, and share download links via email. Files auto-expire and self-delete.
A UX/UI mobile app prototype for a modern restaurant built in Figma. Designed for seamless reservations, food ordering, dietary filtering, and real-time delivery tracking across diverse user personas.
Full-stack restaurant management system with a customer ordering portal and admin dashboard — featuring menu management, order processing, role-based auth, and real-time analytics.
An interactive Shiny dashboard analysing tech job opportunities across the UK from 2019–2023 — visualising shifts in roles, skills, salaries, and regional hiring patterns.
A web-based security scanner for any public URL — running 15+ checks including OWASP Top 10, SSL/TLS validation, and HTTP headers, with human-readable results and fix recommendations.
End-to-end e-commerce analytics — raw transactional CSVs cleaned with Python and surfaced in a Looker Studio dashboard tracking sales KPIs, customer behaviour, and product performance.
Predicts a user's future Spotify Wrapped using historical streaming data — applying time-series forecasting for top artists, songs, and listening time, delivered in an animated React UI.
A machine learning model that uses the Naive Bayes algorithm to predict outcomes based on historical data — implemented in Python with scikit-learn for classification tasks.
Let's work together! Send me a message and I'll get back to you as soon as possible.