Resume

MSc Social and Geographic Data Science, Predicted: Merit

• Dissertation on spatial inequality in PMAY-U, India's flagship affordable housing programme: built a national dataset linking Census 2011 slum household counts to homes delivered 2011 to 2025 across 28 states and union territories, plus policy and data governance document analysis.
• Tools and methods: Python (pandas, GeoPandas, scikit-learn), R, SQL; statistical modelling, spatial analysis, graph neural networks (GraphSAGE), NLP (TF-IDF, LDA topic modelling), data visualisation.

BSc (Hons) International Politics, 2:1

• Global Money and Finance (final year): the dollar system, money and capital markets, securitisation, leverage, corporate debt and central bank policy (QE, interest rates).
• Assessed work: 2,500-word essay on the problems of modern central banking (stagflation, QE, independence); group case pitch on BRICS de-dollarisation; presented on central bank digital currencies at a role-play Bretton Woods conference.
• Quantified partisan framing across hundreds of media sources using a structured coding framework.

Data and Operations Intern

• Cleaned and summarised datasets and kept operational data accurate for a UK politics and sports prediction platform.
• Developed pub and creator partnership pitches for 2026 World Cup activations and ran 2 live viewer events, adding 100+ users (around 15% growth).

Office Administrative Assistant

• Processed rental documents for 60 properties, handling sensitive tenant information with close attention to detail.
• Maintained records and databases and coordinated with residents, contractors and internal stakeholders.

Assistant Editor

• Interviewed 2 sitting MPs, including a minister, and Liberal Democrat, Labour, Green and independent candidates during the 2024 general election.
• Edited political and economic news to tight deadlines and coordinated election coverage with local organisations.

Summer Intern

• Researched UK immigration law and distilled complex legal and policy material into a concise report for senior staff.

Work Experience (Financial and Risk)

• Traced an error in a stock's listing data with Eikon's data team and helped troubleshoot client data exchange issues.

• Built an end-to-end pipeline joining Land Registry, Census and deprivation data for 4,833 London neighbourhoods, engineering a spatial adjacency graph of 26,552 edges so that comparable neighbouring areas inform each price prediction.
• Benchmarked 4 models on held-out data: GraphSAGE reached R² 0.767 and MAE £88k, cutting error by 28% versus a linear baseline and 14% versus a non-spatial neural network.

• Classified 82,182 Yelp reviews of 5,234 Calgary businesses using text, sentiment and structured features; logistic regression reached 0.88 accuracy and 0.86 macro-F1.
• Topic modelling showed poor service drove negative reviews; combined sentiment with local competition to recommend an underserved south-east Calgary area for a new restaurant.

• Built and run a live public tracker of 456 platform restrictions across 79 countries and territories, covering 49 platforms and backed by 171 cited sources.

• Co-organised Rangeela 2026, a sell-out West End showcase with 200+ performers, and represented postgraduates.

• Co-led the first Students' Union South Asian Fair, managing logistics, budgets and external partners end to end.