Summary
Lukas Borke is a Berlin-based system administrator and data scientist with over a decade of professional experience and more than 20 years of programming background. He blends rigorous statistical training (PhD-level work in statistics) with hands-on expertise in Linux operations, cloud deployments, and AI/visual search systems. Lukas has led deep learning research and productionization efforts—rapid prototyping in Python and Docker to deployment with C# and AWS—while also advising on financial markets and quantitative models. His long-standing focus on stochastic methods and practical finance tooling means he evaluates trends skeptically: hypes fade but robust models like Black–Scholes and S&P500 analysis endure. Comfortable across academia, startups, and enterprise stacks, he brings a rare mix of theoretical rigor and production discipline to AppOps and ML-driven products. Colleagues rely on him for solving high-compute vision problems and translating statistical ideas into reliable, scalable systems.
10 years of coding experience
4 years of employment as a software developer
Doctor of Economic Sciences (Ph.D.) in the field of Statistics Ladislaus von Bortkiewicz Chair of Statistics, Doctor of Economic Sciences (Ph.D.) in the field of Statistics Ladislaus von Bortkiewicz Chair of Statistics at Humboldt-Universität zu Berlin
Diplom-Mathematiker Hauptfach: Mathematik Nebenfach: Informatik, Diplom-Mathematiker Hauptfach: Mathematik Nebenfach: Informatik at Leibniz Universität Hannover
German, English, Russian, French