Full Stack Developer passionate about AI and ML,
bringing code to life — from the first line to final deployment.
Hi there!
I’m Celest, a Software Engineer passionate about creating impactful solutions at the intersection of AI, machine learning, and software development.
My experience spans data engineering, analytics, and software development, enabling me to tackle complex challenges and deliver impactful results. With hands-on experience across diverse projects, I focus on bridging the gap between technical execution and business objectives. I have developed data-driven solutions, optimised processes, and built scalable software systems to address a wide range of problems.
Outside of work, you’ll likely find me either on the squash or tennis courts, out on the golf course, or brainstorming my next project.
Let’s connect and chat!

HCLTech
Full-stack Java and PeopleSoft Developer, specialising in the optimisation and enhancement of campus solutions.
Dow Jones
Streamlined workflows with Python automation and a login interface, saving over 10 hours of manual work weekly.
Cheil Singapore
Automated multilingual data pipelines with Python for Samsung Galaxy Z Series, saving 20+ hours of manual work monthly.
Handshakes by DC Frontiers
Developed 3 real-time monitoring dashboards in PowerBI, integrated with REST APIs to optimise scalability.

An NLP-based application that processes text data to detect languages, clean input, and generate translations. The app automatically identifies the language, preprocesses the data, and translates it into the desired target language.

Spring Boot-based banking application that includes user registration, authentication, account management, and transaction handling. Built with Figma, Angular, Spring, and MySQL.

An AI-driven application that solves Sudoku puzzles by capturing and processing images. Using image recognition, the app detects and extracts the Sudoku grid, interprets each cell, and applies a solving algorithm to complete the puzzle.

An analytical application designed to uncover patterns and key factors influencing airline delays. Developed using both Python and R, it performs in-depth data exploration, visualizes trends, and identifies critical insights such as seasonality, carrier performance, and delay hotspots to support data-driven decision-making.
I’m always up for a conversation about shared
passions. Let’s connect and see where our
interests take us!