About

I'm Ivan Gorban, a Staff Data Scientist working at the intersection of machine learning, causal inference, experimentation, and applied AI. My work is mostly about turning ambiguous product and business problems into models, metrics, experiments, and decision systems — especially in marketplace environments where prediction alone is rarely enough.

I've been at Careem (an Uber company) since 2022, promoted to Staff Data Scientist in 2025. My work spans the full arc from early prototyping to production systems: dynamic pricing for the QUIK grocery vertical, a captain churn-prevention system, adaptive ETA prediction, a marketplace simulation environment, and an experimentation platform I've operated across data science, engineering, and product management functions.

Before that, I led a team of data scientists and business analysts at MegaFon, one of Russia's major telecom operators, working on retail-network strategy, pricing, and a reinforcement-learning-based next-best-action system. Earlier, at Pompeu Fabra University's Social Media Group in Barcelona, I worked on network science and social media analysis — groundwork for the causal inference intuitions I use today.

I write about causal inference, experimentation, AI, automation, and the economic and educational consequences of new technology — aiming to make technical ideas clear without flattening them into slogans, and to connect methods with the real decisions they're supposed to support.