I'm a Data Scientist based in Manchester, working across machine learning, data analysis, and BI. I have an MSc in Data Science and came into the field from a Physics background which is probably why I still care more about whether a model or pipeline actually holds up than about how it looks in a slide deck.
Day to day I move between two modes: analyst work (SQL, KPI frameworks, digging into why a number moved) and ML work (building and validating models other people end up relying on). This profile is where I share the projects behind that mostly Python, SQL, and Tableau/Power BI, plus a couple of things I built just because I wanted to understand them better.
- Analysis & BI: SQL-based data modelling, KPI frameworks, and root-cause investigation on large (1M+ row) datasets; dashboards in Power BI and Tableau
- Machine learning: classification, regression, ensemble methods, and NLP with scikit-learn, PyTorch, XGBoost, and LightGBM
- Data engineering: ETL pipeline design, data validation, and workflow automation in Python and SQL
- Databases: relational modelling and query optimisation in PostgreSQL and MySQL
- MetroMove Transit Analytics: end-to-end Python EDA optimizing fleet scheduling and pricing
- Sales Performance Analysis: a Tableau dashboard built to surface where profit was actually leaking, not just to look nice
- Salary Benchmarking Prediction: regression pipeline predicting tech salaries across five countries, with NLP-driven feature engineering
- Spam Detection (NLP): TF-IDF + SVM spam classifier, deployed as a Streamlit app
- Freelance Gig Analysis: a look at a $10M freelance marketplace: revenue, talent performance, and market scalability
- Fuzzy Logic Interactive Tool: a small web app teaching fuzzy logic through worked demos, built alongside my dissertation
Open to Data Scientist / Data Analyst / ML Engineer roles and happy to walk through any of the above in more detail.
