Jul 2026 — Present
Founding Data Scientist
Book Depot Inc. · Thorold, Ontario
I own pricing intelligence across a 60K+ SKU catalog: elasticity, causal DML, inventory pacing, and the unglamorous work of making those models survive a real catalog.
About
Who I am
I am Hassan Mehmood, an AI/ML Engineer & AI Systems Architect. I live in the part of the work where a model has to become a decision: a price, a match, a flag, a posture. I like that part more than the demo.
I have about three years of shipping ML, data platforms, and BI in fintech and B2B shops. Before that I taught. I still think like someone who has to explain the thing out loud.
My journey
Health sciences first. Then markets, analytics, models, and the systems that keep models from becoming folklore. I did not plan the path as a brand. It is just what kept being interesting.
- Business Analytics ↓
- Data Science ↓
- Machine Learning ↓
- ML Engineering ↓
- AI Systems ↓
- Quantitative Finance ↓
- Building
What I build
Sep 2025 — Jul 2026
Data Scientist
Iteration Matrix · Remote
Production ML for supplier mastering, ROI attribution, and audit recovery. Reporting errors went from 25% to under 5%. I also owned the MLOps path: CI/CD, containers, retraining, drift, monitoring.
May 2025 — Aug 2025
Data Science Analyst
EQ Bank · Toronto, Ontario
Automated ETL and live Power BI for model performance. Cut manual reporting by about 90%. Built a multithreaded Polars quality system over more than 1TB of SQL Server data.
Sep 2022 — Aug 2024
Instructional Specialist, Data Analytics & FinTech
University of Toronto · Remote
Mentored 50+ students through Python, SQL, machine learning, and time series. I like teaching the parts people usually skip: why the model is lying, and what to do next.
What I'm learning
Tighter identification in pricing. Evaluation for agents that is not theatre. How much of a quantitative system can stay local and still be serious.
What I'm interested in
Causal ML, production systems, capital markets as a measurement problem, and teaching people who are done collecting certificates.
Currently thinking about
Causal ML that has to price real things
Elasticity is easy to estimate and hard to trust. I keep coming back to confounding, inventory, and the gap between a notebook and a catalog.
Agents as systems, not demos
A loop that calls tools is not an architecture. I am more interested in memory, evaluation, and what happens when the agent is wrong on a Tuesday.
Markets as a measurement problem
Macro regimes, analogues, and position sizing. Less prediction theater, more evidence.
What an AI business actually sells
Not a model. A decision, a workflow, and a way to know when it stopped working.
School and paper
Master's, Business Analytics & AI
Ontario Tech University · 2025
3.99 / 4.3
A.I. Solutions Development
George Brown College · 2024
Dean's Honor List
Financial Technology
University of Toronto · 2022
Bachelor's, Health Sciences
University of Health Sciences, Pakistan · 2015
Also: IBM Data Engineering, IBM Full Stack, Azure Data Scientist Associate, EDHEC investment management with Python and ML. Useful stamps. Not the work.