Joel Persson — Research Scientist, AI & Economics, Spotify

I am a Research Scientist in AI & Economics lab at Spotify. My research focuses on causal inference, statistical ML/AI, and data-driven decision-making, with applications to experimentation, personalization, and digital platforms.

At Spotify, I work on how to improve the efficiency and effectiveness of online experimentation and offline policy evaluation, including how AI can augment traditional approaches. The tools I have helped developed support internal testing and product decisions and run in production on Spotify Home and our experimentation platform.

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 contributed as technical advisor and program lead at Algorithm Audit.

I hold master's and bachelor's degrees in Statistics and Business & Economics from Lund University, Sweden. Before my PhD, I worked on marketing mix models at GfK (acquired by NielsenIQ) and in performance marketing at Precis Digital.