Hi, and welcome to my website.

I am a Research Scientist at Spotify. My interests are broadly in causal inference and data-driven decision-making using statistical and machine learning methods, with applications to digital experimentation, personalization, online platforms, and related domains. At Spotify, I work on contextual bandits, off-policy evaluation and heterogenous treatment effects, most recently for optimizing training and evaluation of recommender systems powered by AI.

I hold a PhD from the Department of Management, Technology, and Economics at ETH Zurich. My supervisors were Stefan Feuerriegel and Florian von Wangenheim. During my PhD, I visited the Operations, Information & Technology area at Stanford Graduate School of Business, hosted by Jann Spiess, and interned as Machine Learning Researcher at Booking.com in Amsterdam. I also joined Algorithm Audit as a technical contributor. 

Previously, I obtained double BSc and MSc degrees in Statistics and Business & Economics from Lund University, Sweden, and worked as Marketing Scientist at GfK (now part of Nielsen) and as analyst at an award-winning digital marketing agency.