Anita Bahmanyar is a Senior AI Scientist with 13 years of experience blending astrophysics research and production-grade data science to solve complex problems in both academic and financial sectors. Currently finishing a PhD in Astrophysics at the University of Toronto, she leverages supernovae Type Ia and LSST simulations to probe cosmic structure while translating those statistical and pipeline skills into advanced threat detection and AI systems at CIBC. Her work spans end-to-end data engineering, probabilistic modeling, and scalable ML—having built cleaning pipelines, simulation tests, and classification metrics for international collaborations and Kaggle challenges. She brings a rare combination of observational cosmology expertise and hands-on production experience converting Pandas workflows to PySpark and deploying deep learning models for image classification. Known for rigorous validation and reproducible pipelines, she excels at turning noisy, domain-specific data into robust, deployable insights.
12 years of coding experience
13 years of employment as a software developer
Master of Science - MS Astronomy and Astrophysics, Master of Science - MS Astronomy and Astrophysics at University of Toronto
Diploma Physics and Mathematics, Diploma Physics and Mathematics at National Organization for Development of Exceptional Talents (Sampad)
A validation framework and tests for mock galaxy catalogs and beyond
Contributions:16 pushes, 1 branch in 2 years 6 months
validation-frameworkvalidationcatalogsgalaxymock
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