Lorenz Walthert
Data Scientist
Zurich, Zurich, Switzerland
Summary
🤩
Rockstar🎓
Top SchoolLorenz Walthert is a data scientist and ML/Ops engineer based in Zurich with 11 years of professional experience and 7+ years focused on building end-to-end machine learning systems. He has led ML Ops design as a founding team member at UrbanDataLab, operationalizing models with MLflow, Databricks, SageMaker and Docker on AWS while working extensively in R and Python. An active open-source contributor, he maintains the widely used R formatter styler on CRAN and has contributed R support and testing to high-profile projects like mlflow and pre-commit, improving reproducibility and cross-language tooling. His background blends applied spatial data pipelines, package development, and automation, and he brings a rare combination of production-grade engineering and R ecosystem stewardship. Outside work, he’s passionate about climate action and integrates that mission-driven perspective into his tooling and project choices.
11 years of coding experience
4 years of employment as a software developer
Bachelor of Arts (B.A.) HSG, Bachelor of Arts (B.A.) HSG at Universität St.Gallen - Hochschule für Wirtschafts-, Rechts- und SozialwissenschaftenMaster’s Degree, Master’s Degree at ETH ZürichExchange Student at McIntire School of Commerce, University of Virginia, Exchange Student at McIntire School of Commerce, University of Virginia at McIntire School of Commerce
Stackoverflow
4,569reputation
341kreached
19answers
17questions
lazy-evaluation
top-1%
r
top-5%
dplyr
top-5%
Github Skills (23)
xgboost10
python10
r10
mlflow10
precommit10
pre-commit-hook10
lazy-evaluation10
test-automation10
git9
machine-learning9
model-management9
dplyr9
documentation8
linter8
refactoring7
Programming languages (25)
Github contributions (5)
mlflow/mlflow
Dec 2019 - Mar 2021
Open source platform for the machine learning lifecycle
Role in this project:
Back-end Developer & Test Automation Engineer
Back-end Developer & Test Automation EngineerContributions:28 reviews, 19 commits, 20 PRs in 1 year 3 months
Contributions summary:Lorenz primarily contributed to the R package for the MLflow project. Their work involved fixing issues related to artifact listing in the R package, ensuring correct file size attributes. They also regenerated R documentation, added a package help file, and addressed errors. Furthermore, the user added and maintained R tests and supported XGBoost integration within the MLflow R package.
pythonlifecyclemlmachine-learningincremental-learning
pre-commit/pre-commit
Feb 2021 - Dec 2022
A framework for managing and maintaining multi-language pre-commit hooks.
Role in this project:Back-end Developer
Back-end DeveloperContributions:13 reviews, 12 commits, 10 PRs in 1 year 10 months
Contributions summary:Lorenz primarily contributed to adding and improving support for the R programming language within the pre-commit framework. They focused on integrating R through the `renv` package, enabling dependency management and environment isolation for R hooks. Their work involved implementing the installation and execution logic for R hooks, including handling dependencies, setting up the environment, and ensuring proper execution of R scripts within the pre-commit framework. The contributions demonstrate expertise in integrating a new language, R, into a Python-based framework and incorporating tools like `renv` for reproducible builds.
linterpythonmulti-languagepre-commitrefactoring
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