About

I am a graduate student at the London School of Economics, completing an MPA in Data Science for Public Policy. My work sits at the intersection of applied econometrics, machine learning, and spatial analysis, with applications in economic development, sovereign risk assessment, and market analysis. I am a native Italian and Croatian speaker, fluent in English, with conversational French.

My current capstone project, in partnership with Moody's Ratings, builds a country-level classification of sovereign exposure to natural resource dependency across 208 economies. The pipeline merges USGS mineral production data, World Bank development indicators, and UN Comtrade trade flows, applying clustering, decision trees, and regularised regression to identify which resource-rich countries manage to diversify and which do not. The output is designed to inform transition finance risk assessments for sovereign debt analysts.

Other recent work includes regime-switching analysis of US monetary policy rules using 70 years of Federal Reserve data, spatial demand analysis of ride-hailing markets in New York City, and a classification pipeline for gender-based pricing in UK supermarket products. Before LSE, my undergraduate dissertation at Bocconi used fixed-effects panel models to examine geographic variation in credit access for financially constrained firms across Northern Italian provinces.

Outside of academic work, I serve as Senior Editor for Podcasts at The Public Sphere Journal (LSE School of Public Policy), producing and editing long-form academic interviews that structure complex research for non-specialist audiences. I also designed a quantitative scoring methodology for an interactive political matching tool used in the 2024 European Parliament elections in Greece, which generated over 10,000 completed surveys and ranked first on Google for related search terms.

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