Viktor Lázár is an associate in risk analytics at Morgan Stanley with 14 years of cross-disciplinary experience blending AI, financial mathematics and policy research. He builds trustworthy machine learning and risk models with a focus on provable guarantees and auditability, bringing theoretical rigor from his PhD-level computer science training and an MA in Financial and Economical Mathematics. Viktor has steered multi-partner research projects on AI adoption and regional innovation competitiveness, presented at the European Parliament and international summits, and led teams translating economic and technological research into policy insights. His background spans hands-on quant work—model calibration, sensitivity analytics and automation in Python/SQL/VBA—to executive-level strategic analysis as professional secretary to a national research office. Based in Budapest, he pairs academic depth with practical implementation in finance and governance, uniquely positioning him at the intersection of model risk, AI governance, and innovation policy. Colleagues describe him as methodical, integrity-driven, and unusually comfortable moving between code, theory and high-level strategy.
13 years of coding experience
1 year of employment as a software developer
Business and Economics - Leadership, Business and Economics - Leadership at Mathias Corvinus Collegium - MCC
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Eötvös Loránd University
Real Estate Finance and Investments, Real Estate Finance and Investments at ESCP Business School
Master of Arts - MA, Financial and Economical Mathematics, Master of Arts - MA, Financial and Economical Mathematics at Corvinus University of Budapest
Contributions:4 commits, 3 pushes, 1 branch in 1 year 6 months
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