Simeon Carstens
Data Software GenAI All-kinds-of-things Engineer Data Scientist
Paris, Ile-de-France
Summary
🤩
Rockstar🎓
Top SchoolSimeon Carstens is a data and software engineer with 14 years’ experience bridging computational structural biology and production data systems, currently based in Paris and working at Tweag I/O. He combines deep Bayesian and MCMC expertise from academic postdocs with practical cloud, infrastructure-as-code and GenAI engineering to help scientists and industry tame large, heterogeneous datasets. At Tweag he moves fluidly between technical roles—engineer, team lead, solution designer and pre-sales—across genomics, education and operations, shipping reproducible pipelines in Python, Nix and Nextflow. His open-source contributions include improving TensorFlow Probability examples and tests, reflecting a focus on robust probabilistic tooling for real workloads. Colleagues value his ability to translate complex statistical methods into scalable, testable software that runs on HPC and cloud alike.
13 years of coding experience
7 years of employment as a software developer
Master of Science (MS), Physics, Master of Science (MS), Physics at University of TübingenDoctor of Philosophy (PhD), Computer Science, Doctor of Philosophy (PhD), Computer Science at Technical University of Munich
English, French, German, Italian
Stackoverflow
3reputation
628reached
0answers
1question
Github Skills (12)
mcmc10
machine-learning10
probabilistic-programming10
tensorflow10
python10
statistics9
bayesian-methods9
deep-learning8
data-science8
neural-network7
memoryview6
cython6
Programming languages (9)
Github contributions (5)
tensorflow/probability
Jul 2020 - Aug 2020
Probabilistic reasoning and statistical analysis in TensorFlow
Role in this project:
ML Engineer
ML EngineerContributions:9 commits, 2 PRs, 9 comments in 14 days
Contributions summary:Simeon primarily contributed to improving the documentation and examples within the `tensorflow/probability` repository. Their work involved fixing errors in existing examples related to the `ReplicaExchangeMC` method, including issues with data types, plotting, and deprecated arguments. Furthermore, the user refactored the code to adapt `ReplicaExchangeMC` to use `get_field()`/`update_field()` for more flexible kernel nesting and improved the clarity of error messages within the codebase. They also added tests for newly implemented utility functions and enhanced the robustness of the testing framework.
statisticspythonprobabilistic-reasoningdata-sciencedeep-learning
tweag/chainsail
Jan 2021 - Mar 2023
Contributions:25 reviews, 254 commits, 43 PRs in 2 years 2 months
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