Summary
Sebastian Hohmann is a Senior Data Scientist and economist with over eight years of experience turning large structured and unstructured datasets into actionable models for finance and policy. He has built production-grade risk models — from equity VaR and mortgage PDs to price-movement forecasting from order book data — and now applies that expertise at UBS after roles at Deloitte and academic institutions. Comfortable bridging research and engineering, he automates pipelines in Python, teaches geospatial analytics, and has processed datasets exceeding 100 million rows. His PhD-trained causal-inference background informs rigorous model design and real-world decision-making, evidenced by work estimating COVID-19 excess mortality and advising pricing strategy for insurers. Based in Zürich, he combines deep quantitative thought with a practical focus on reproducible code and deployable analytics.
7 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy - PhD, Economics, Doctor of Philosophy - PhD, Economics at London Business School
Master, International Economics, 6/6, Master, International Economics, 6/6 at Graduate Institute of International and Development Studies
Bachelor of Arts - BA, European Studies, 1st Class Honours, Bachelor of Arts - BA, European Studies, 1st Class Honours at King's College London