Summary
Mehrdad Mohammadi is a data scientist with a decade of experience blending rigorous statistical training and full-stack development to solve real-world problems. Currently at Bayer, he applies machine learning to industry-scale datasets after research roles at UIUC’s Bioacoustics Lab where he supported an NIH-funded R01 project. He holds advanced degrees in economics, statistics, and mathematics—including a PhD in Statistics from UIUC—and brings a rare mix of econometric thinking and applied ML practice. Comfortable shipping end-to-end solutions, he pairs production engineering instincts from his GitHub work with deep inferential modeling skills developed in academic research. An interesting facet: his background spans accounting and finance through to advanced statistics, enabling him to translate domain constraints into robust predictive systems.
10 years of coding experience
1 year of employment as a software developer
Bachelor’s Degree, Accounting and Finance, Bachelor’s Degree, Accounting and Finance at Petroleum University of Technology
University of Bologna
Master of Arts - MA, Economics (Econometrics and Quantitative Economics), Master of Arts - MA, Economics (Econometrics and Quantitative Economics) at Penn State University
Master of Science - MS, Statistics, Master of Science - MS, Statistics at University of Illinois Urbana-Champaign
English, Persian, Kurdish, Italian