Joel Persson — Research Scientist, AI & Economics, Spotify

I am a Research Scientist in the AI & Economics lab at Spotify. My research focuses on statistical and machine learning methods for causal inference and data-driven decision-making, with applications in the digital economy.

At Spotify, I work on problems at the interface of online experimentation, off-policy evaluation, and LLMs as surrogates for user outcomes and preferences. The tools and systems I have helped develop run in production on the Spotify homepage and our internal 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.