Building the in-person socialising network.

Part of the Exchange at Department accelerator programme for digital and tech startups

Member of the esteemed network of software leaders.

Validated Young Professionals demand to meet new people by growing a meetup community to over 3000 members with 100+ attendees per event.

Engineered an industry search tool using ChatGPT to augment data, enhancing the investment prospecting process while gaining insights into the capabilities and drawback of LLMs.Attuned to internal customer needs, collaborated closely with financial analysts to craft an MVP replicating an intricate Excel tool, expediting company comparison and financial analysis.Delivered iterative product demos for stakeholders, optimising communication, and heightening stakeholder engagement.

Designing from the ground up a Data Pipeline to use various APIs to keep a single source of truth Data Warehouse updated. Implemented on AWS EKS with Prefect as Kubernetes orchestrater, dbt as the data modelling tool and Data Visualisation through Tableau. Also oversaw a cultural change from manually fulfilling ad-hock urgent data requests to agile development of self-serve systems empowering non-technical co-workers to access data they need. Involved in the development of agile process management, codifying SOPs (Standard Operating Procedures) and helping reduce WIP (Work In Progress). Managed a Junior Engineer, helping them progress from adhock Python scripts to fully tested, documentated (with type hints), function and class based Python packages.

I worked as part of the fledgling Data Science chapter of Crimson Macaw, helping derive insights into clients data and provide actionable value which can be automated through machine learning. Completing AWS Cloud Practitioner and AWS Cloud Solutions Architect Associate certifications in just 6 week. These have enabled me to understand cloud native data solutions and explore how MLOps can allows data science solution to be implemented as part of a consistent repeatable micro-service architecture. I also got familiar with AWS SageMaker and Hugging Face to develop a product review analysis system that was visualised in AWS QuickSight and pitched to our technology partners. Alongside these skills I also learnt how Crimson Macaw use Snowflake, dbt and Terraform to provide our clients reliable solutions.

I worked in the Materials Innovation Factory (MIF), a world-leading research facility, with Unilever on their dedicated floor in the building, in the team responsible for automation and standardisation of the laboratory robots, equipment and data pipelines. Through the Unilever’s in house data entry systems, I worked processing the data that the laboratory equipment produces. Developing my Python skills as I wrote scripts to process outputs from the robots used across MIF, to simplify the regular generation of visualisations that provide at a glance, up to date details of critical metrics. Through communication with colleagues with a chemistry background, to understand what goes into making Unilever products, I was able to extract the questions that they would like visualisations of the data to help them answer. I worked with Power BI to develop a variety of models and visualisation of Unilever and Competitor products to provide insight into the direction for further research and development.

Responsible for working with managing updates and replacements of next-generation technologies on computers running essential laboratory and automation equipment throughout the Materials Innovation Factory (MIF). Worked with colleagues across the MIF to make sure vital data was not lost and that downtime, while improvements were made, was limited to the bare minimum.

I spent my summer studying Deep Learning with the guidance of my research project supervisor. I built, tested and trained Machine Learning models, gaining an understanding of Deep Learning, Neural Networks theory and fluency in Python. My research was focused on Graph Neural Networks, a novel form of Artificial Intelligence that focuses on developing and understanding algorithms that will work with Non-Euclidian data such as social networks, sensor networks and point clouds. I implemented cutting edge models by reviewing leading current academic research on GNNs required to work with Non-Euclidian data. I gained familiarity with Pandas and other python data science packages, as well as a deep understanding of PyTorch as I worked to understand the implementation of the PyTorch Geometric extension library. I continued this project in my final year of university, working specifically point clouds that have the potential to provide improved performance over current standard Euclidian data-based computer vison. I have also built a working knowledge Linux systems using bash and Slurm Workload Manager on the universities High-Performance Computing cluster.

I am started work as a part of a two-person team of a night. Responsible for checking in and out customers using opera and tasked with preparing the hotel for the next day. I then transferred to afternoon shifts and dealt with more customer interaction on the reception desk.

Casual contract - lifeguard and general leisure centre duties in customer facing role, including poolside, general housekeeping duties and reception.

Lifeguard and general leisure centre duties in customer facing role, including poolside, first aid, setting up pool events including equipment set-up and assisting duty manager carrying out lock up checks and locking up facility.