I am a Research Scientist in the AI & Economics lab at Spotify. My research interests are primarily in causal inference and data-driven decision-making in digital settings. Most of my work develops methods for applied research and practice, grounded in statistical, econometric, and machine learning theory. At Spotify, I develop tools and systems for efficient and effective online and offline experimentation, most recently for settings where AI is used to generate and evaluate product innovations.

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.