Experience
My professional journey through data science, machine learning and computer science challenges.
Technical Proficiency
Machine Learning & AI
Data Analysis & Visualisation
Statistical Modeling
Languages
Database & Cloud
Web Development
Tools
Certifications
Microsoft Certified: Machine Learning Operations Engineer Associate
Microsoft • August 2026
Validated skills in designing and implementing MLOps and GenAIOps infrastructure, managing machine learning model lifecycles, and monitoring and optimising AI systems in Azure.
Microsoft Certified: Azure AI Engineer Associate
Microsoft • June 2026
Validated skills in designing and implementing Azure AI solutions using Azure AI services, Azure AI Search and Azure OpenAI.
Microsoft Certified: Azure Data Scientist Associate
Microsoft • June 2025
Validated expertise in implementing and running machine learning workloads, particularly in the Azure cloud environment.
Microsoft Certified: Azure AI Fundamentals
Microsoft • March 2025
Demonstrated foundational knowledge of machine learning and artificial intelligence concepts and related Microsoft Azure services.
Chronology
Tech, Data & Analytics Senior Associate
At PwC my work has sat at the intersection of data science, machine learning, AI engineering and data engineering for financial services, cyber and technology clients. I started as a technology degree apprentice in Leeds, building SQL pipelines, interactive dashboards and forecasting models, before rejoining as an Associate in London in August 2024 and being promoted to Senior Associate in July 2025. Since then I have taken on more complex technical delivery and workstream ownership, including reusable Python and SQL reconciliation pipelines for PSD2 Transaction Risk Analysis reviews, processing and reconciling over 10 million daily banking transactions across major banking clients within strict regulatory audit requirements. I also contributed to an Azure-based RAG/LLM extraction solution for unstructured provider PDFs and PowerPoint documents, reducing manual processing by 85% and improving extraction accuracy by 10%. On the modelling side, I developed scikit-learn forecasting models for offshore delivery-centre resource demand, improving forecast accuracy by 20% and saving around 25 hours of manual work each month, as well as regression-style models for resource and capital expenditure that supported a 10% operational cost reduction opportunity. I have also built forecasting models for Cyber revenue and sales-pipeline planning, visualised through Power BI, and applied NLP and sentiment analysis to 250+ Law Firm Survey responses to turn structured and free-text data into report-ready insights. Across these projects I have had to make model outputs, data limitations and AI trade-offs clear through technical workshops, model walkthroughs and senior stakeholder presentations.
BSc Computer Science (Digital & Technology Solutions)
I completed a Level 6 Digital and Technology Solutions Degree Apprenticeship with PwC. Awarded a 2:1 (Upper Second-Class Honours) overall, including first-class grades in Machine Learning, Information Visualisation and Data Science modules. I also achieved a first-class grade in my dissertation on probabilistic football event machine learning models.
International Baccalaureate Diploma Programme
I studied the International Baccalaureate Diploma Programme at Sixth Form and was awarded 43 out of 45 points (Triple A* A-Level equivalent). I studied Computer Science (7), Economics (7) and English (7) at Higher Level alongside Latin (7), Mathematics (6) and Classics (6) at Standard Level.
GCSEs
I achieved seven Level 9s, two Level 8s, one Level 7 and one A grade at GCSE. My Level 9 subjects included Computer Science, English Literature, Geography, History, Biology, Chemistry and Physics. I also studied Mathematics (level 8), Latin (level 8), English Language (level 7) and Japanese (grade A).