Analytics Architect
Thomas graduated from KU Leuven in 2025 with a Master in Information Management and Economic Policy.
Throughout his studies, he developed a strong interest in addressing economic questions through data-driven and empirical methods. His academic background provided him with experience in database management, ETL processes, data visualization, machine learning, process modelling and mining, and econometrics. In addition to his academic work, Thomas completed several internships, gaining hands-on experience in business intelligence, data integration, and applied analytics in real-world settings.
His first master’s thesis examined the impact of resampling techniques on the performance of machine learning models for credit card fraud detection. His second thesis explored the role of collective bargaining centralization in modelling international export flows using econometric methods.
Outside of his professional interests, Thomas enjoys staying informed about current economic developments, exploring advancements in AI, hiking, keeping active, and following NBA basketball and football.
Thomas joined element61 in March 2026.
