hi there —
Waterloo · open to Winter '27 co-ops

I'm a data scientist
turning messy data into
quiet, useful things.

I'm a third-year at the University of Waterloo studying statistics, drawn to big data pipelines, small local models, and shipping software that people actually use.

Based in Waterloo, ON
Studying Statistics · UW '28
Focus Big data · ML · full-stack
01 / About

A short note
about me.

The quick version. Longer one lives on my LinkedIn.

I grew up taking things apart and (eventually) putting them back together. These days the "things" are data pipelines, ML models, and small pieces of software that sit between them.

I like to build products that won't just be generic, off-the-shelf — I'd rather ship something creative that solves a problem people didn't know they had. Bonus points if the data is inconveniently large and a simple pandas.read_csv won't cut it.

Outside of class I build for hackathons (four and counting), spend time at the gym bettering myself in ways school can't measure, and travel whenever I can — Japan is up next this fall.

02 / Experience

Places I've
learned things.

A running log of co-ops, research, and teaching — in reverse chronological order.

Jan 2026 — Present

Junior Data Analyst Co-op

— Natural Resources Canada

Building new tools with senior mentorship to streamline internal data analysis, including parallelized workflows with MPI. Producing models, visualizations, and dashboards that situate Canada's position against global events in relation to energy, forestry, and mining commodities.

Ottawa, ON
Jul — Aug 2025

Data Analyst Intern

— Fresh Idea Collective

Cleaned and integrated external financial datasets in Excel, VBA, and Power BI with seasonal-adjustment transforms feeding the firm's microeconomic analysis. Lifted master-depot data quality by ~18% and presented case-study findings to PMs and advisors.

Stratford, ON
May — Jul 2025

Internal Systems Contractor

— AudienceView

Automated legacy content migration in Python (pandas, Selenium, BeautifulSoup) with a 1:1 link-matching pass, cutting manual work by 95%+. Refactored 1,000+ Salesforce Knowledge articles, trimming customer lookup time ~40%.

Toronto, ON
May — Sep 2024

Software Developer Intern

— Kuala Lumpur Kepong Berhad

Built ASP.NET/Blazor data-entry forms backed by SQL Server and CRUD APIs, automating 1,000+ leave and 5,000+ business requests annually. Added observability to the EMS, reducing MTTD by ~25%.

Kuala Lumpur, MY

↳ Full resume on request — drop me a line.

03 / Selected Projects

Things I've
made recently.

Mostly hackathon builds — rough edges intact. Each was an excuse to learn something new.

04 / Bookshelf

Books that shaped
how I think.

The titles I keep returning to — the backbone of my data science roadmap.

05 / Now

What's on my
desk this week.

Updated whenever I remember to. — last touched 4/19

Reading

  • Python for Data Science Handbook
    Jake VanderPlas · fundamentals first
    ★★★★★
  • Introduction to Statistical Learning
    James, Witten, Hastie & Tibshirani
    ★★★★★
  • Hands-On ML with Scikit-Learn, Keras & TensorFlow
    Aurélien Géron · applied practice
    ★★★★☆
  • Deep Learning with Python, 3e
    Chollet & Watson · up next
    ★★★★☆

↳ full roadmap: dsRoadMap

Learning / building

  • Sharpening data science fundamentals
    Statistics, ML theory, and the math that glues them
  • Shipping a data-driven side project
    End-to-end: ingest → model → dashboard
  • Going to the gym, distantly
    Showing up three days a week this term
let's talk —

Say hello.

sean.lee1@uwaterloo.ca