February 2026 - Present | United Kingdom, Manchester
January 2025 - February 2026 | United Kingdom, Manchester
July 2023 - January 2025 | United Kingdom, Manchester
June 2022 - June 2024 | Remote
June 2014 - April 2016 | United Kingdom, London
Combining my passion for Data Science and Football. In this project I use Bayesian Modelling to predict Premier League football match wins.
A Reddit Sentiment Analysis Streamlit Application. Users can search for a subreddit and get a sentiment summary of all posts and comments in the subreddit. Users can also see trends in sentiment.
An end to end book recommendation system. Built a search engine using cosine similarity that allows users to search for books, rate them and create user profiles. Book recommendations are then created using collaborative filtering.
Published 5 android games to the Google Playstore. 'Blizard' got 1000 downloads and 'Platform' had an average rating of 4/5 stars. Self taught game development at 14.
I write about data-intensive systems, machine learning, and MLOps.
Jan 2025 · Data Engineer Things
Understanding the theory behind Apache Kafka for managing real-time streams.
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Jun 2025 · Towards AI
A production-focused RAG system exploring MLOps and LLMOps best practices with open-source tools.
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Jul 2024
Types 0 to 3, and how to choose the right SCD strategy in data engineering.
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September 2019 - June 2023 | United Kingdom, London
Subject: B.Sc. (Hons) in Mathematics
Grade: First Class ~ 4.0 GPA
Modules: Linear Algebra, Vector Calculus, Partial Differential Equations, Optimization, Bayesian Inference, Linear Models, Financial Time Series etc.
Final Year Dissertation: Modelling the risk of violent crime in London using Bayesian Spatial Temporal Models. My dissertation involved a niche application of Bayesian Spatial Temporal Models to analyze violent crime in London, focusing on identifying spatial and temporal crime patterns.
MATH1151
Coursework for MATH1151 Partial Differential Equations. Coursework involved solving the wave equation using Python.
MATH1189
Involved Bayesian statistical analysis using JAGS for regression, Gibbs sampling, and logistic regression for the Challenger study which emphasized predicting O-ring failure at varying temperatures.
MATH1122
Coursework for MATH1122 Financial Time Series. Involved exploratory analysis of SP500 data. Analysed log returns and performed Jarque and Bera test for normality. Tested for ARCH effects using the Lagrange Multiplier Statistic and fit ARCH(1) and GARCH(1,1) models.
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