Glory Ogbonda

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I am a data scientist and a full-stack developer with a passion for creating data-driven solutions that drive business results and social impact. I have years of experience in analysing complex data sets, developing predictive models, and designing interactive visualisations using a wide range of technologies and techniques, such as machine learning, data visualisation, and statistical analysis. Currently, I am pursuing a PhD in Computer Science at Bangor University, as part of the UKRI CDT in Artificial Intelligence, Machine Learning and Advanced Computing, where I am conducting a research on the use of AI in visualising the UK public law. I am also a Senior data analyst at Qrapp Technology, where I conduct extensive data analysis to identify key trends and patterns in customer behaviour, resulting in a 10% increase in customer engagement. Additionally, I am a lead software developer at Tawa Online, where I use Javascript, AngularJS, ReactJS, MarionetteJS, BackboneJS, and NodeJS to develop and maintain web applications and services. I am seeking a challenging role in a dynamic organisation where I can apply my skills and expertise to drive meaningful impact. I am adept at using various tools and frameworks, such as Mapbox, D3.js, MongoDB, SQL server, Git, and CI/CD architecture. I am also a certified software professional and a co-author of two publications in Eurographics Digital Library. I have a strong background in information technology and business informative systems, having obtained my bachelor's and master's degrees from Middlesex and Bangor University , and two diplomas from NIIT Pune.
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Hello, I’m Ebube Glory Ogbonda, Data Scientist, Full Stack Developer Based in the United Kingdom. See link for Web CV
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Data engineer passionate about Data Science 📊. I like automating, building scalable pipelines, and improving and optimizing systems. I am a Strong Advocate for 📜 open source, ☁️ Cloud computing, 🚀 DevOps, 🆕 Innovation and Automation 🤖 🌱 I’m currently pursuing Masters in Advanced Computer Science at Bangor University, UK ⚡ Fun fact: I am a firm believer in the Chaos theory, which states that even in unpredictable environments with seemingly random oddities and irregularities, there exists a predictable and sensible pattern that is not initially visible. 💡 I'm interested in all things data: Big Data, Cloud, Machine, Deep and Reinforcement Learning, Data Science and Visualizations 💬 Talk to me about Formula 1 🏎️, Memes, Anime, Movies 🎥, Call of Duty 🎮, Amateur Photography 📸

Education/Academic qualification

Postgraduate, MSc, Master of Science Advanced Computer Science (Computer Science) , Bangor University

18 Sept 2022 → 31 Aug 2023

Award Date: 31 Aug 2023

Undergraduate, BSc, Bachelor's degree Information Technology and Business Informative Systems (Computer Science), Middlesex University

20 Jan 2014 → 16 Aug 2018

Award Date: 16 Aug 2018

Professional, Professional, Professional Diploma in Information Technology ( Software Engineering ) (Computer Science), NIIT (National Institute of information technology)

20 Jun 2015 → 24 Nov 2017

Award Date: 24 Nov 2017

Postgraduate, PhD, Doctor of Philosophy - PhD Computer Science (Artificial Intelligence Machine Learning and Advanced Computing CDT) (Computer Science), Bangor University

22 Sept 2023 → 31 Aug 2027

Postgraduate, Other, Non Degree (Visiting) (Physics (Quantum Computing), Swansea University

23 Mar 2024 → …

Postgraduate, Non Degree (Visiting) PGR (2PHYS028R) (School of Physics (Machine Learning), Bristol University

8 Oct 2023 → …

Postgraduate, Other, Non Degree (Occasional Studies) (Cardiff School of Physics & Astronomy (Astrophysics Data Analysis), Cardiff University

8 Oct 2023 → …

Postgraduate, Other, Non Degree (Visiting) (Computer Science (Research Methods), Canolfan Adnoddau Prifysgol Aberstwyth

18 Sept 2023 → …

Explanatory Visualization with LLMs for Employment Law
Ogbonda, G., Nason, S., Roberts, J. C. & Butcher, P., 24 Jul 2025.
Research output: Contribution to conference › Poster › peer-review

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Glory Ogbonda

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Research output

Explanatory Visualization with LLMs for Employment Law