Summary
Andreas Grafberger is a research software engineer with nine years of experience applying machine learning and software engineering to production and research environments across Europe. He holds an MSc with high distinction from the Technical University of Munich and recently published his first lead-author conference paper, signaling strong research chops alongside production impact. His career spans fast-paced industrial teams at Amazon and MSCI—where he worked on data quality, anomaly detection, and climate risk systems—and academic roles building visualization and ML tooling. Comfortable across Python, Scala, Spark, Vue.js and D3, he has a track record of porting core systems to modern stacks and shipping production-ready anomaly detection used in live pipelines. Now based in Germany and open to roles in Germany and the Netherlands, he blends rigorous research thinking with pragmatic engineering to move models and data services into robust, scalable systems. Notably, he has experience consulting cross-border teams to automate large-scale data quality verification, demonstrating both technical depth and collaborative leadership.
9 years of coding experience
3 years of employment as a software developer
Master of Science (with high distinction) Informatics, Master of Science (with high distinction) Informatics at Technical University of Munich
Bachelor of Science Computer Science, Bachelor of Science Computer Science at University of Augsburg
German, English, Italian, French, Japanese, Spanish