Jan-benedikt Jagusch is a pragmatic data engineer with 8 years of experience building ML-driven data products and reliable ETL pipelines, currently working at QuantCo in Heidelberg. He has led and mentored small data science teams, shipping production document-classification, topic modelling, search and recommendation systems while improving code quality, testing and CI/CD practices. His open-source contributions span conda-forge automation, ONNX model conversion improvements for LightGBM, and packaging work for Jupyter tooling — demonstrating a mix of DevOps, ML engineering and backend expertise. Academically strong with master’s-level training in information management and international exposure from studies in the US and Germany, he combines rigorous modeling skills with practical deployment know-how. A detail-oriented engineer, he often focuses on build automation and model-conversion edge cases that quietly reduce production friction.
8 years of coding experience
2 years of employment as a software developer
Business IT, 1.1 (GPA: 3.9), Business IT, 1.1 (GPA: 3.9) at University of Tennessee-Knoxville
Master of Science, Information Management - Business Intelligence, 19 / 20 (GPA 4.0), Master of Science, Information Management - Business Intelligence, 19 / 20 (GPA 4.0) at NOVA IMS Information management school
Bachelor of Science (B.Sc.), International Management for Business and Information Technology, 1.6 (GPA: 3.5), Bachelor of Science (B.Sc.), International Management for Business and Information Technology, 1.6 (GPA: 3.5) at Duale Hochschule Baden-Württemberg
Jupyter notebook server extension to proxy web services.
Role in this project:
Back-end Developer
Contributions:16 reviews, 41 commits, 2 PRs in 1 month
Contributions summary:Jan-benedikt focused on modifying the `setup.py` file, a key configuration file for the project. Their contributions included adding and removing dependencies, updating metadata, and adjusting data file configurations. These changes aimed to ensure the correct installation and operation of the jupyter-server-proxy extension, addressing aspects like package dependencies, project metadata, and data file inclusion. Furthermore, they integrated co-authored changes, specifically in updates to the `setup.py` file.
A place to submit conda recipes before they become fully fledged conda-forge feedstocks
Role in this project:
DevOps Engineer & Automation Engineer
Contributions:116 reviews, 98 commits, 63 PRs in 1 year 9 months
Contributions summary:Jan-benedikt primarily focused on automating and configuring the build and deployment process for various conda recipes within the conda-forge ecosystem. Their contributions involve modifying build scripts (build.sh and bld.bat), integrating Go-based tools such as dockle and grype, and managing licensing information. Furthermore, the user made changes to integrate with CI/CD services, including setting up environment variables and token rotations. The changes are related to automating the build and integration of recipes into the conda-forge system.
placeconda-forgerecipescondasubmit
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