Business Analytics · Data Analytics & ML · Python · SQL · Power BI
I bridge an Electrical Engineering foundation with applied data analytics — building end-to-end workflows from raw data pipelines to statistical models and interactive dashboards. Currently based in Toronto, open to analytics roles and research collaborations.
I'm a Business Analytics student at Seneca Polytechnic with a B.Eng. in Electrical & Electronics Engineering from Iran University of Science & Technology (IUST). My engineering background shaped how I approach problems: systematically, with attention to data quality, model validity, and communicable results. I'm currently focused on analytics projects involving data preparation, regime-based modeling, machine learning, and dashboard design — and I'm actively looking for a role where I can apply these skills in a real-world data team.
Languages, frameworks, and platforms I work with.
A quick look at three pieces of work I’m proud of. Each one started with a real question, went through the messy data work, and ended with something useful — a model, a dashboard, or a public-facing data story people can actually understand.
Transit Analytics · Python · SAS · Tableau · Dash
A regime-based analysis of Toronto TTC ridership showing how travel demand changed before, during, and after COVID. The project combines open data, feature engineering, statistical modeling, and dashboard storytelling to explain not only how much ridership recovered, but what now drives it.
ML Recommender · Python · NLP · Embeddings · Clustering
A personalized movie recommendation system built from a user watchlist and a 50,000-title candidate pool. The project uses enriched movie metadata, semantic text embeddings, rating-aware user profiles, and taste-stream clustering to recommend films beyond platform-specific popularity bubbles.
Data Storytelling · Public Safety Analytics · Visualization · The Analyst
A public-facing data article for The Analyst that turns ten years of Toronto intimate partner and family violence records into a clear story about persistence, place, timing, and prevention. The goal was not just to show charts, but to make the patterns specific enough to understand and act on.
Professional background spanning engineering, data analysis, and editorial leadership.
Interdisciplinary foundation combining engineering rigor with applied business analytics.
Professional development through IBM, Coursera, and LinkedIn Learning programs.
Open to data analytics roles, internships, and research collaborations.