Resume

Education

University of Sussex, (Sep 2020 – May 2024)

I have graduated with a BSc in Computer Science and Artificial Intelligence with First-Class Honours. My time at Sussex has been nothing short of extraordinary, the culture at Sussex has allowed me to cultivate a great skillset, gaining both technical and non-technical skills. During my undergraduate degree, lecturers have been very open to having conversations regarding my career and my research interests, which played a great part in laying the foundations for where I want my future career to go.

I’ve taken part in multiple extracurriculars, having rebuilt the Computer Science Society, HackSussex website from the ground up in React, to becoming the Vice President responsible for leading a team of 20 students, managing new workflows and honing leadership skills. I also presented the annual coding competition at Sussex, and assisted in organising the HackSussex GameJam and HackSussex’s biggest hackathon to date, with over 200 attendees! I have been a Teaching Assistant for artificial intelligence related modules such as Natural Language Engineering, Computer Vision and Acquired Intelligence & Adaptive Behaviour. I’ve also been a Peer Assisted Learning (PAL) Tutor, working with a team of 15 to host programming support workshops, organise talks on growing a career within the tech space and facilitate weekly drop-in sessions to assist students in debugging code.

My Bachelor’s Thesis is “Post-Inventory Announcement Forecasting in the Crude Oil Market with Machine Learning”, and has been an interesting journey, it involves taking the U.S. Crude Oil Inventories weekly announcement and forecasting both the inventory value itself as well as the market movement proceeding the event using a neural network that takes multiple features including natural language such as breaking financial news headlines into account to improve it’s prediciton.

Career

Software Engineer, Macquarie, (Jul 2024 – Present)

Joined the Corporate Operations Group Division Graduate program.

Junior Research Associate, University of Sussex, (May 2023 – Sep 2023)

During the Summer of 2023, I embarked on a research journey to find a correlation between the semantics of breaking financial news headlines and market movement across the world. Some of the key learning points from this project was that retrieving financial data is difficult, as it is often behind a paywall. This makes your models susceptible to having poor performance as garbage in tends to be garbage out. Through this project I gained a lot of skills related to data engineering, computational finance and machine learning. I used pandas for data engineering, LangChain to interact with my models and storing time series in an SQL database, and word embeddings in a vector database.

The results of this project come in two parts, the first is the neural network-driven interactive map made with nomic.ai where you can filter the headlines by tag or words, and check the metadata such as the timestamp, headline title, price difference and volatility before and after different time frames. The second half was an automatic tagging tool, since we had headlines dating back to 2012, only the last few years had tags associated with them, by training and hyperparameter optimising (with Bayesian optimisation) a neural network model we were able to predict tags of unseen headlines with 90% accuracy.

Software Engineer Intern, Thought Machine, (Jul 2022 – Sep 2022)

In my freshman year of University in 2022, I interned at a fast-moving cloud native core banking scale up, Thought Machine. I was placed in the payments department where I worked on a library that is deployed in production to validate client-configured payment processes, using graph theory, test-driven development, Protocol Buffers, Please build system and written in Go. Afterwards, I put forward an idea via a design document, collaborating with product managers, software engineers and site reliability engineers to monitor how the library was being used, allowing for a positive product feedback loop to improve documentation surrounding the limitations of payment flows based on common errors.

Software Engineer, FinancialJuice, (Jul 2020 – Dec 2021)

FinancialJuice served as my introduction to both Natural Language Processing and Finance. My projects at FinancialJuice included grouping together semantically similar headlines, using a Jaro-Winkler algorithm, and creating a trending news feature similar to X’s (formely Twitter) based on a Bag of Words and keyword searching algorithm made with C#. Implemented the algorithm into a usable web component for in-house analysts with Microsoft Azure, jQuery and .NET, that utimately improved headline output by 25%.

Junior Software Engineer, Tradeviews, (Dec 2018 – Aug 2020)

My first job in tech involved automatic data collection with web scraping in Python, and data engineering to transform the data into a coherent format such as CSV JSON and XLSX, and pipelining the data using Pentaho so it could be shipped to clients. I increased the data sources by 150% and with more data products we were able to secure 4 new major clients.

Technical Skills

Fields of Expertise

The areas of Computer Science I have relevant expertise in includes Machine Learning, Natural Language Processing, Deep Learning, Data Processing, Computational Finance, Test-Driven Development, Data Visualisation, Algorithmic Trading

Languages

I most often program using Python, C++ and Golang. I have working profciency with C++, C#, C, Java, VBA

Technologies

I have used a variety of technologies and try to keep up with relevant technolgies, my current toolkit includes React, Node.js, Linux, AWS, jQuery, Latex, Git, Pentaho, MySQL, Microsoft SQL Server, Bootstrap