Dr. Irena Bojarovska
Irena Bojarovska is an Applied Scientist at Zalando SE, focusing on time‑series forecasting and demand prediction across 24+ markets.
Originally from Macedonia, she earned a BSc and an MSc in Applied Mathematics and Computer Science in Russia and a PhD in Applied Harmonic Analysis from TU Berlin. She began her industry career as an analyst at Air Berlin and, since 2017, has worked on causal inference for marketing, automation, demand forecasting, hierarchical reconciliation, and time‑series foundation models at Zalando. Outside work she leads a math circle for children at Lyzeum 2 and enjoys spending time with her family.
Session
The rise of time-series foundation models like Chronos-2 and TimesFM has sparked a debate: can a single pre-trained model replace the specialized "local" models we have tuned for years? We moved beyond the hype to test these models in production-like environments, from high-level market trends to granular article-level demand. In this talk, we share a transparent look at our journey: the zero-shot capabilities of these models, the reality of fine-tuning with exogenous business drivers, and a comparison between generative models and state-of-the-art classical methods. We categorize what is currently possible, what remains a challenge, and provide a roadmap for teams looking to integrate foundation models into their forecasting stack without sacrificing reliability.