About
Hi, I’m Jason Schmidberger
Protein crystallographer turned data scientist. I design probabilistic models and ML pipelines for real-world sensing problems—lately methane emissions analytics and spatial anomaly detection. My toolkit spans Python (NumPy/Pandas/PyMC), Bayesian inference, Gaussian plume modeling, and cloud/HPC delivery.
- Focus – uncertainty-aware analytics, stakeholder-ready insight, and clean, reproducible engineering.
- Experience – 20+ years across academia and industry in Australia, Sweden, Scotland, and the UK.
- Impact – built RJ-MCMC workflows that localize leaks, automated reporting aligned with OGMP 2.0, and taught teams modern data-science practices.