Hi, my name is Joel (Swedish pronunciation "yo-el") and welcome to my website.

I am a Research Scientist in the Machine Learning and Economics lab at Spotify. My research interests are in causal inference, statistical machine learning, and data-driven decision-making, in particular for applications in digital platforms, marketing, health and related areas transformed by personalization and digitalization. 

At Spotify, I lead research and development in methods for heterogeneous treatment effects, contextual bandits, and off-policy evaluation to optimize personalization and experimentation in large-scale recommender systems.

I hold a PhD from the Department of Management, Technology, and Economics at ETH Zurich, supervised by 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, interned as ML Research Scientist at Booking.com in Amsterdam, and joined the non-profit startup Algorithm Audit as a Core Contributor on statistical methodology. Previously, I earned double BSc and MSc degrees in Statistics and Business & Economics from Lund University, Sweden, and worked at GfK Nielsen and an award-winning European digital advertising agency.