Hauke Krämer is an Associate Director in Data Science with eight years of experience bridging theoretical physics and applied AI to build production-grade NLP and document-extraction products. Trained as a summa cum laude PhD in theoretical physics, he migrated from cutting-edge time-series and dynamical-systems research (neural ODEs, recurrence analysis, causal inference) into enterprise ML at EY, where he leads retrieval-augmented agentic workflows and fine-tuning of SLMs/LLMs for long-context, visually rich documents and finance automation. He simultaneously holds an active research role at the Potsdam Institute for Climate Impact Research, keeping a foot in method development such as Monte Carlo Tree Search for state-space reconstruction. Known for curating robust training and test sets and embedding state-of-the-art models into production stacks, he combines rigorous scientific thinking with pragmatic product delivery. An unusual strength is his fluency in both principled dynamical-systems methods and hands-on model fine-tuning, enabling rare end-to-end ownership from theory to deployed workflows. Based in Freiburg, Germany, he excels at translating complex research techniques into business-impacting AI solutions.
8 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD, Theoretical Physics, Summa cum laude, Doctor of Philosophy - PhD, Theoretical Physics, Summa cum laude at Universität Potsdam
Staatsexamen, Physics, Staatsexamen, Physics at Albert-Ludwigs-Universität Freiburg im Breisgau
Contributions:2 releases, 123 commits, 2 PRs in 1 year 5 months
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