I am a Software Engineer currently training with CodeYourFuture, transitioning into tech from a background in Economics and financial auditing (CFA Level II).
I am now focusing on applying to software development. I am working hard to build a solid foundation in full-stack JavaScript, writing clear code, and learning how to properly test applications.
I am currently looking for full-stack, backend, or software engineering roles where I can leverage my economics/accounting/finance background alongside my engineering toolkit.
- Location: Liverpool, UK (Open to Hybrid / Remote)
- Email: tzemingho@gmail.com
- LinkedIn: Connect with me on LinkedIn
- Languages: JavaScript (ES6+), SQL, HTML5, CSS3, Python, Java(currently learning)
- Backend & Databases: Node.js, Express, SQL
- Frontend Development: React, HTML5, CSS3
- Tools & Testing Environment: Git/GitHub, Docker, Ubuntu Linux, Jest, Node:Test
A collaborative application built to manage shared digital resources with strict attention to data integrity and UX.
- Tech Stack: JavaScript, LocalStorage, CSS3
- Key Highlights: Implemented URL validation and
crypto.randomUUID()to prevent indexing collisions. Achieved a 100% Lighthouse Accessibility score via semantic HTML and ARIA implementation. - Live Experience: Explore the Live Demo
A collaborative tool engineered to compute complex, recurring calendar dates and generate standardized schedule configurations.
- Tech Stack: JavaScript, Node:Test
- Key Highlights: Engineered complex date-calculation logic to seamlessly handle custom annual patterns (e.g., "Second Tuesday of October") while accurately accounting for leap year edge cases. Built a shared logic layer used across both the frontend and an automated iCal generator script.
- Live Experience: Explore the Live Demo
An individual data-analysis project designed to parse and extract valuable insights from high-volume datasets.
- Tech Stack: JavaScript (ES6), JSON
- Key Highlights: Formulated custom manipulation algorithms using advanced JS array methods and maps to parse large JSON sets, isolating specific time-based listening habits (e.g., identifying "Friday night" user trends).
- Live Experience: Explore the Live Demo