Building applied AI systems that drive measurable business impact.
Principal Data Scientist with 10+ years designing, building, and deploying production-grade machine learning, optimization, forecasting, and AI solutions across retail, healthcare, and public-sector environments.
What I Do
Core capability areas across applied AI/ML and decision science.
GenAI & Agentic AI
Agentic RAG systems, LLM fine-tuning (LoRA/QLoRA), embeddings, orchestration, evaluation workflows, context engineering, and AI architectures.
Machine Learning & Deep Learning
Recommender systems, time-series forecasting, classification, and regression using bagging and boosting algorithms.
Operations Research & Optimization
Linear programming, mixed-integer programming, discrete-event simulation, approximate dynamic programming, and multi-criteria decision analysis.
About
I'm a Principal Data Scientist with a PhD in Operations Research and 10+ years of experience designing and deploying production-grade AI/ML solutions. Currently at Canadian Tire Corporation, I build recommender systems, production ML models, optimization engines, and agentic AI systems across retail operations.
My work spans the full analytical lifecycle — from data ingestion and feature engineering to model development, validation, deployment, and stakeholder communication. I bring deep expertise in Python, SQL, Spark, Databricks, and MLflow, with a strong track record of translating ambiguous business problems into scalable solutions and measurable outcomes.