Data Analyst · Business Analytics
I turn complex datasets into clear, commercially relevant decisions — combining Python, SQL, and machine learning with a sharp eye for data storytelling and stakeholder impact. Previously at JPMorgan Chase and 180 Degrees Consulting.
I'm a Data Analyst with hands-on experience across e-commerce, financial services, and market intelligence, built through projects with real clients and measurable outcomes.
At J.P. Morgan Chase, I worked in fraud detection at scale, contributing to the prevention of $1M+ in quarterly losses and reducing investigation turnaround by 60% through data and process analysis. At 180 Degrees Consulting, I applied the same analytical rigour to market intelligence: segmenting competitors, scoring leads, and producing client-ready frameworks that fed directly into commercial strategy.
I hold an MSc in Business Analytics from Durham University (Merit, Scholarship recipient), with formal training in machine learning, statistical modelling, and predictive analytics. My background in business gives me a broader lens on the work. I approach analysis with an understanding of commercial context, stakeholder priorities, and the decisions the data ultimately needs to support.
End-to-end customer analytics on 1M+ UK e-commerce transactions. RFM segmentation, churn prediction, CLV modelling and campaign attribution — outputting a £12,500/month Google Ads + Klaviyo strategy.
Analysed 40k+ business records using Python to identify structural patterns in customer and competitor data. Segmented organisations into actionable profiles via clustering, with multi-year trend analysis to surface high-growth regions and strategic expansion opportunities.
Quantitative research suite covering commodity forecasting, contract pricing, credit risk ML, and optimisation algorithms. Completed as part of JPMorgan's virtual Quantitative Research programme.
Analysed financial time series data to assess stationarity and trend behaviour using statistical testing. Applied differencing and rolling averages to extract underlying trends from volatile datasets. Built reproducible preprocessing workflows to support consistent reporting.
View on GitHubOpen to Data Analyst and Business Analyst roles in London and beyond. Also available for freelance analytics and consulting projects. Legally authorised to work in the UK.