I am a Research Scientist in the AI & Economics lab at Spotify. My research is broadly in statistics, econometrics, and machine learning, with a focus on applications to causal inference and data-driven decision-making in the digital economy.

At Spotify, I lead research and development in methods for more efficient and effective experimentation, evaluation, and training of recommender systems, including how generative AI can augment traditional approaches.

I received my PhD from ETH Zurich in 2024, advised by Stefan Feuerriegel and Florian von Wangenheim. During my doctorate, I visited the Operations, Information, and Technology group at Stanford GSB, hosted by Jann Spiess, and interned as Machine Learning 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.