I am a Research Scientist in the AI & Economics team at Spotify. My research is broadly in econometrics and machine learning, with a focus on applications in data-driven decision-making. At Spotify, I develop systems and tooling for more efficient and effective causal inference and experimentation in recommender systems, including the use of generative AI.

I received my PhD in Management (Information Systems and Quantitative Marketing) from ETH Zurich in 2024, advised by Stefan Feuerriegel and Florian von Wangenheim. My doctoral research focused on causal inference and machine learning methods, with applications in digital platforms, media, and health. During my doctorate, I visited Stanford GSB, hosted by Jann Spiess, and interned as a Research Scientist at Booking.com. I also contribute to the nonprofit Algorithm Audit.

I hold master's and bachelor's degrees in Statistics and Business & Economics from Lund University, Sweden. Before my PhD, I worked in marketing science at GfK (acquired by NielsenIQ) and in performance marketing at Precis Digital.