Moritz Wilksch
Data Scientist
Berlin, Germany
Summary
🤩
Rockstar🎓
Top SchoolMoritz Wilksch is a Data Scientist based in Berlin with six years of experience building production-ready ML solutions and data engineering workflows. He combines a strong academic background in Business Informatics and Interdisciplinary Data Science with hands-on expertise in Python, PyTorch/Keras, HuggingFace, XGBoost/LightGBM, and orchestration tools like Prefect, Ray and Dask. At QuantCo he applies ML engineering practices across models and services, while his open-source work includes package build automation for conda-forge and improving documentation and examples for the high-performance Polars dataframe library. Comfortable across SQL, Spark, NoSQL and cloud platforms (AWS/GCP), he also maintains a niche sentiment-analysis library for financial social media, blending domain knowledge with engineering rigor. Notably, his contributions bridge pragmatic build/release automation and user-focused library UX—helping complex tooling become accessible to others.
6 years of coding experience
1 year of employment as a software developer
Master in Interdisciplinary Data Science, Data Science, Master in Interdisciplinary Data Science, Data Science at Duke UniversityBachelor of Science - BS, Business Informatics, 1,4, Bachelor of Science - BS, Business Informatics, 1,4 at University of Potsdam
German, English, French
Stackoverflow
191reputation
19kreached
13answers
0questions
Github Skills (31)
conda-forge10
build-script10
cargo10
python10
dataframes10
polar10
cicd10
dataframe10
automation10
polars10
automations10
rust10
frame10
documentation10
go9
Programming languages (12)
Github contributions (5)
pola-rs/polars
Feb 2022 - Sep 2022
Dataframes powered by a multithreaded, vectorized query engine, written in Rust
Role in this project:
Back-end Developer
Back-end DeveloperContributions:3 reviews, 12 commits, 23 PRs in 6 months
Contributions summary:Moritz primarily contributed to adding and improving documentation examples within the Python codebase of the polars library. They focused on providing practical usage examples for various DataFrame and Expr methods, enhancing the usability and clarity of the documentation. Their changes involved modifying docstrings in `py-polars/polars/internals/frame.py`, `py-polars/polars/internals/expr.py`, `py-polars/polars/internals/lazy_frame.py` and other Python files to include illustrative code snippets. These improvements showcase their commitment to user experience and knowledge of the library's API.
polarsdataframespythondataframerust
conda-forge/staged-recipes
Oct 2023 - Mar 2025
A place to submit conda recipes before they become fully fledged conda-forge feedstocks
Role in this project:Automation Engineer / Build & Release Engineer
Automation Engineer / Build & Release EngineerContributions:15 reviews, 34 PRs, 66 comments in 1 year 5 months
Contributions summary:Moritz primarily contributed to setting up and modifying build scripts for various conda-forge recipes. Their work included adding build scripts for new packages like `uuid-utils`, `hugo`, `silicon`, `polars-distance`, `jd`, `fastmod`, `jfrog-cli`, `speedscope`, `d2`, `television`, `sqruff`, `aichat`, `httptap`, `py-rust-stemmers`, and `baml-py`, often involving cargo, go, and python build processes. They also made changes to existing build configurations, demonstrating a focus on package build automation and dependency management within the conda-forge environment.
placeconda-forgerecipescondasubmit
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