Yabra Muvdi is a data analyst and economist with eight years of experience building practical ML and analytics solutions across academia, government, and industry from Switzerland. They have delivered production-ready systems — from recommender engines for the Swiss government to LLM-based information extraction for the Inter‑American Development Bank — and consulted on pipelines that cut transcription time by 95% and qualitative analysis time by 50%. At ETH Zürich and UCL they translated cutting‑edge research into teaching and widely used datasets and tools cited by over 120 publications and adopted by 800+ researchers. Comfortable bridging research and product, they design custom retrievers, RAG systems and predictive models that prioritize automation and measurable impact. Their background in economics informs a focus on policy-relevant metrics and evaluation, while a voluntary conclusion of a PhD in Data Science & Economics signals intellectual breadth and independence. Fluent in turning unstructured text into decision-ready insights, they combine rigorous research instincts with hands-on engineering to drive cost and time efficiencies.
9 years of coding experience
4 years of employment as a software developer
Master's degree, Data Science, 8.57/10.0, Master's degree, Data Science, 8.57/10.0 at Barcelona Graduate School of Economics
Doctor of Philosophy - PhD, Data Science and Economics, Voluntarily concluded, Doctor of Philosophy - PhD, Data Science and Economics, Voluntarily concluded at ETH Zürich
Contributions:19 pushes, 1 branch in 4 years 7 months
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