Brad Szasz
Staff Data Scientist
San Jose, California, United States
Summary
👤
Senior🎓
Top SchoolBrad Szasz is a Staff Data Scientist based in San Jose with nine years of experience building production-ready, readable, and scalable data systems. He brings a rare blend of academic rigor—holding a PhD in Ecology and Evolutionary Biology—and industry impact, applying Bayesian GLMMs, stochastic simulations, time-series, and quantitative genetics to real-world problems. At Mozilla he moved from Senior Inference Data Scientist to Staff, after roles leading data teams and engineering efforts that turned experimental models into deployed ML systems. His research on invasive species and epidemic modeling has been featured in major outlets and produced novel models that outperformed common epidemiological approaches. Comfortable across the stack, he has led sensor-driven machine learning projects in agriculture and built consumer-facing forecasting tools for international markets. Colleagues rely on him for principled modeling that balances theoretical insight with practical, production-grade implementation.
9 years of coding experience
12 years of employment as a software developer
MRes (with Distinction) Ecology and Evolutionary Biology, MRes (with Distinction) Ecology and Evolutionary Biology at University of NottinghamDoctor of Philosophy Ecology and Evolutionary Biology, Doctor of Philosophy Ecology and Evolutionary Biology at Rice UniversityBS Biomedical Engineering (Minor in Mechanical Engineering), BS Biomedical Engineering (Minor in Mechanical Engineering) at University of Rochester
Github Skills (47)
looker10
recall10
r-package9
spark9
python9
data-warehouse9
etl-framework9
mozilla9
telemetry9
sql-database8
data-analytics8
etl8
airflow8
big-data8
bigquery8
Programming languages (7)
Github contributions (5)
bochocki/bochocki.github.io
Jun 2019 - Apr 2024
My personal/professional website
Contributions:34 PRs, 93 pushes, 11 branches in 4 years 11 months
professional-websiteprofessionalnextjs
bochocki/correlatedtraits
May 2017 - Mar 2019
A laboratory experiment and simulation to measure the impact of trait correlations on evolution during invasions
Contributions:4 PRs, 41 pushes, 4 branches in 1 year 10 months
evolutiontraitcorrelationslaboratorysimulation
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