David Ochsenbein
Senior Director Process Science Modeling & Data
Zurich, Zurich, Switzerland
Summary
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Senior🎓
Top SchoolDavid Ochsenbein is a Senior Director specializing in process science, modeling, and data with an 11-year track record of applying first-principles and machine learning approaches to pharmaceutical development and manufacturing. He has led projects that delivered over $10M in savings by enabling lean tech transfers, real-time release, and anomaly detection across clinical and supply-chain operations. With a PhD in Chemical Engineering from ETH Zurich and hands-on roles at Janssen, Novartis, and Johnson & Johnson Innovative Medicine, he combines deep domain knowledge with pragmatic data science to accelerate delivery of better drugs. David is equally focused on the human side of innovation, actively seeking diverse collaborators to turn models into operational impact. An understated strength is his ability to translate complex mechanistic models into robust, production-ready analytics that drive measurable cost and time reductions.
11 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy (PhD) Chemical Engineering, Doctor of Philosophy (PhD) Chemical Engineering at ETH Zürich
German, English, Italian, Portuguese
Stackoverflow
53reputation
2kreached
4answers
3questions
Github Skills (52)
water9
stochastic9
quantile9
stochastic-processes9
python7
scientific-computing6
dictionary6
noaa6
azure-databricks6
databricks6
forloop6
dataframe6
pandas6
aggregate6
science5
Programming languages (6)
Github contributions (5)
SPL-ethz/CAT
Jan 2015 - Aug 2018
Contributions:27 pushes, 11 comments, 31 issues in 3 years 7 months
SPL-ethz/snow
May 2021 - Jun 2022
A Python package describing Stochastic Nucleation of Water in vials
Contributions:5 reviews, 177 commits, 13 PRs in 1 year 1 month
pythonfreezingpharmaceutical-manufacturingscientific-computingquantile
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