Georg Walther
Data Science
Berlin, Germany
Summary
👤
Senior🎓
Top SchoolGeorg Walther is a data scientist with 13 years' experience building production-grade ML systems at the intersection of electricity markets, grid physics, and large-scale analytics. Based in Berlin, he has led data strategy and ML teams, designed Azure- and Kubernetes-based deployment stacks, and delivered time-series anomaly detection, reinforcement-learning trading agents, and recommender systems for enterprise clients. A co-founder with deep research roots (PhD work that produced open-source NetworkX contributions), he combines rigorous numerical and graph-theoretic modeling with pragmatic engineering—authoring performant Python and C components and CI/CD pipelines. His open-source contributions include adding clique-detection functionality to NetworkX and C-based algorithm implementations for coding interview repositories, reflecting both academic depth and hands-on algorithmic skill. Known for turning complex scientific problems into robust, scalable products, he brings a rare mix of domain expertise in energy systems and end-to-end ML delivery.
13 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Computational Biology, Doctor of Philosophy (Ph.D.), Computational Biology at John Innes CentreData Science Fellowship, Data Science Fellowship at Science 2 Data ScienceMaster of Science (MSc), Computational Biology, Master of Science (MSc), Computational Biology at ETH Zürich
Github Skills (15)
text-manipulation10
c1710
algorithm10
data-structures10
algorithms10
quicksort10
graph-algorithms10
strings10
networkx10
c1110
python10
data-structure10
graph-theory10
testing10
graph-analysis9
Programming languages (10)
Github contributions (5)
networkx/networkx
Jan 2013 - Dec 2013
Network Analysis in Python
Role in this project:
Back-end Developer
Back-end DeveloperContributions:8 commits in 10 months
Contributions summary:Georg implemented a new function `get_all_cliques` and a helper method `greater_neighbors` in the `networkx/algorithms/clique.py` file. They refactored and formatted the docstring, and changed the output format for discovered cliques. The user also wrote and added a testing file to confirm the output of the get_all_cliques method.
graph-analysispythoncomplex-networksgraph-theorygraph-visualization
careercup/ctci
Sep 2013 - Sep 2013
Cracking the Coding Interview, 5th Edition
Role in this project:Backend Developer
Backend DeveloperContributions:9 commits in 2 days
Contributions summary:Georg contributed solutions to coding interview questions from "Cracking the Coding Interview," specifically focusing on C language implementations. Their work includes implementing algorithms like determining unique characters in a string, reversing a string, and implementing a quicksort function. The user also wrote test cases for these functions to validate their correctness. The contributions directly address fundamental data structure and algorithm concepts relevant to software engineering interviews.
cpp5th-editionc-plus-pluscracking-the-coding-interviewcracking
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