Summary
Milad Rezazadeh is a Lead Data Scientist with 11 years of experience building production-grade ML systems at RBC, with deep expertise in MLOps, NLP/LLMs, anomaly detection and time-series forecasting applied to financial risk, fraud prevention and operational integrity. He combines research rigor from a PhD and materials-science background with hands-on engineeringโdesigning cloud-native pipelines, Terraform/Ansible provisioning, and model-serving stacks that have driven automation and multi-million dollar impact. Milad has shipped agentic RAG applications, OCR/NLP solutions for revenue and settlement workflows, and production anomaly detectors that strengthen compliance monitoring. Comfortable across Python, TF/Keras, Hugging Face, SQL and DevOps tools, he excels at turning complex research into auditable, scalable services. Notably, his prior work accelerated materials characterization from weeks to minutes and applied transfer learning to extend IoT forecasting horizons by an order of magnitude, illustrating a pattern of practical innovation.
11 years of coding experience
9 years of employment as a software developer
Amirkabir University of Technology
Master of Science - MSc, Computational Physics/Chemistry, A, Master of Science - MSc, Computational Physics/Chemistry, A at Dalhousie University
Certificate in Data Science, A, Certificate in Data Science, A at University of Toronto
English, Persian