Summary
Ghazal Farhani is a research scientist and data engineer with 11 years of experience translating fundamental physics and astrophysics expertise into practical machine learning and data-analytics solutions for industry and government. Currently at the National Research Council Canada, she focuses on data analytics and ML for autonomous systems, building on prior roles that delivered churn prediction, customer segmentation, content-propensity, graph-anomaly detection, and Bayesian bandit solutions at The Globe and Mail. As a Presidential Data Science Fellow at Western University she taught bootcamps and collaborated across research teams, demonstrating an ability to both mentor and operationalize models. Her PhD in Physics underpins a rigorous, hypothesis-driven approach to modeling complex, real-world systems, and she often blends unsupervised, neural and probabilistic methods in production-ready pipelines. Notably, she pairs deep domain knowledge with practical product impact—driving decisions from customer lifetime value to headline optimization.
10 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD, Physics, Doctor of Philosophy - PhD, Physics at Western University
Bachelor of Science - BS, Physics, Bachelor of Science - BS, Physics at University of Tehran
English, Persian