Summary
Daniel Kaestner is a data-driven founder and engineer with a decade of experience applying machine learning and statistical modeling to real-world systems, from public transport simulation to controlled-environment agriculture. He built virtual plant models and optimized growth formulas for medical crops as Lead Data Scientist at Vertical Farm Tech, and later transitioned into software and AI architecture roles before founding Croplytics. Trained at Maastricht University in Data Science for Decision Making and experienced as a teaching assistant across math and CS courses, he blends rigorous academic grounding with hands-on product delivery. His early work improving the RAPTOR routing algorithm demonstrates a knack for turning theoretical insight into practical runtime and usability improvements. Comfortable across backend development, simulation, and ML pipelines, he focuses on sustainable, data-centric solutions that scale. Based in Karlsruhe, he combines entrepreneurial ambition with a pattern-seeking approach to complex systems.
10 years of coding experience
3 years of employment as a software developer
Master's degree Data Science for Decision Making, Master's degree Data Science for Decision Making at Maastricht University
Computer Science, Computer Science at RWTH Aachen University
German, English, Spanish