Todd Heitmann
Lead Machine Learning Engineer at St. Louis Cardinals
Missouri, United States
Summary
👤
Senior🎓
Top SchoolTodd Heitmann is a Lead Machine Learning Engineer and geoscientist with over a decade of applied experience building production ML platforms and data pipelines across energy and sports organizations. Based in Missouri, he’s led end-to-end data science efforts—from founding data workflows and ML lifecycle platforms at startups to deploying real-time analytics for executive decision-making at Echo Energy and automating reservoir engineering analyses earlier in his career. At the St. Louis Cardinals he bridges advanced analytics with operational needs, applying scientific rigor from his petrophysics and reservoir engineering background to sports analytics problems. He holds an MS in Data Science and a BS in Chemical Engineering, and is notable for translating complex physical modeling (e.g., Monte Carlo reservoir simulations and PDE-based transport models) into scalable Python and SQL production systems.
10 years of coding experience
9 years of employment as a software developer
Lindbergh Sr. High SchoolMaster of Science - MS, Data Science and Analytics, Master of Science - MS, Data Science and Analytics at University of Oklahoma
Github Skills (31)
pii10
viewer10
geostatistics10
las10
geology10
log-viewer9
evaluation9
simulation9
geoscience9
geospatial9
pandas-dataframe9
geopandas9
geography9
open-data9
geophysics9
Programming languages (2)
Github contributions (5)
toddheitmann/mlbgameday
Mar 2017 - Apr 2017
Contributions:22 commits, 20 pushes in 1 month
toddheitmann/PetroPy
Jun 2017 - May 2019
A petrophysics python package for geoscience python computing of conventional and unconventional formation evaluation. Reads las files and creates a pandas dataframe of the log data. Includes a basic petrophysical workflow and a simple log viewer based on XML templates.
Contributions:31 commits, 28 pushes, 2 branches in 1 year 11 months
pythonlog-viewerdata-managementpetrophysicsevaluation
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