I am a Research Scientist in the AI & Economics lab at Spotify. My research interests are broadly in econometrics and machine learning, with a particular focus on causal inference and data-driven decision-making in technology-mediated systems. At Spotify, I work on how to make experimentation, evaluation, and personalization of recommender systems more efficient and effective, most recently when powered with agentic AI.

I received my PhD 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 digitalization. During my doctorate, I visited the Operations, Information, and Technology group at 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.