I am a Research Scientist in the Personalization organization at Spotify, where I work on causal inference, experimentation, econometrics, and machine learning to improve recommender systems and data-driven decision-making. More broadly, my research focuses on bringing methods from these fields to practical applications in digital platforms, digital health, quantitative marketing, and public policy.

I received my PhD from the Department of Management, Technology, and Economics at ETH Zurich in 2024, advised by Stefan Feuerriegel and Florian von Wangenheim. During my doctorate, I visited Stanford Graduate School of Business, hosted by Jann Spiess, and interned as Machine Learning Research Scientist at Booking.com in Amsterdam. I also joined the non-profit organization Algorithm Audit, where I contribute to research and open-source software for bias detection in machine learning systems.

I hold bachelors and masters degrees in Statistics and in Business & Economics from Lund University, Sweden, and previously worked in marketing science and digital advertising.