Gerben Dekker
Gerben is passionate about driving the transition to a sustainable power system. Over 15 years in renewable energy, he transitioned early in his career from consulting to data scientist and machine learning engineer roles, specializing in power systems, electricity markets, wind power, and grid operations across multiple companies. With a strong interest in software engineering design, he has served as both a data scientist and tech lead. He now works at Dexter, where he tackles complex cross-team projects spanning engineering, data science, and energy domain expertise. Dexter provides forecasting and trading services for renewable players in short-term power markets. Gerben holds an MSc in Electrical Engineering from Eindhoven University of Technology.
Session
Monorepos promise faster development and smoother cross-team collaboration, but they often seem intimidating, requiring major tooling, buy-in, and process changes. This talk shows how Dexter gradually introduced a Python monorepo by combining a few lightweight tools with a pragmatic, trust-based approach to adoption. The result is that we can effectively reuse components across our various energy forecasting and trade optimization products. We iterate quicker on bringing our research to production, which benefits our customers and supports the renewable energy transition. After this talk, you’ll walk away with a practical blueprint for introducing a monorepo in your context, without requiring heavy up-front work.