Aamir Khan
Senior MLOps Analyst at Definity
Toronto, Ontario, Canada
Summary
👤
Senior🎓
Top SchoolAamir Khan is a Senior MLOps Analyst based in Toronto with nine years of experience and four years focused on building and productionizing ML and GenAI solutions at Definity Financial. He combines academic depth—a PhD in Computer Science and a UBC Master’s in Data Science—with hands-on expertise deploying end-to-end pipelines on Google Cloud (Vertex AI, BigQuery, Cloud Build) for underwriting, claims, and fraud analytics. At Definity he led large-scale GenAI projects using Gemini and DocAI, won internal innovation awards for RAG and vector search implementations, and helps define company-wide GenAI and development best practices. He also teaches cloud ML courses at McMaster, reflecting a knack for translating complex systems into practical training and production-ready code. Notably, his work has delivered measurable business impact (hundreds of thousands in annual benefits) and operational improvements across insurance and telecom telemetry projects.
9 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Très Honorable (Excellent), Doctor of Philosophy - PhD, Computer Science, Très Honorable (Excellent) at Université Nice Sophia AntipolisMaster's degree, Data Science, 90.4%, Master's degree, Data Science, 90.4% at The University of British ColumbiaBachelor of Science - BSc, Computer lnformation Systems Engineering, A (GPA: 3.68 / 4), Bachelor of Science - BSc, Computer lnformation Systems Engineering, A (GPA: 3.68 / 4) at University of Engineering & Technology Peshawar
French, English, Urdu
Github Skills (12)
anaconda10
language-server-protocol9
spyder9
pyqt9
ide9
python-development8
development-environment8
python8
qt8
heroku2
dashboard2
javascript1
Programming languages (3)
Github contributions (5)
jadoonengr/TemLoPAC
May 2017 - Nov 2019
Contributions:6 pushes, 1 branch in 2 years 6 months
Conrad-Yeung/RAWG.io.Wrapper
Feb 2021 - Feb 2021
Contributions:32 PRs, 50 pushes, 1 branch in 5 days
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