I'm a Statistics and Economics co-op student at the University of Toronto Scarborough, with a minor in English-Chinese Translation. I am preparing for a Fall 2026 work term and am interested in opportunities involving data analysis, reporting, research support, and business or financial operations.

I enjoy turning messy information into clear, usable outputs. My projects combine public data, Python, SQL, dashboards, testing, and practical tools designed for real users.

• Personal website

I use AI as a structured collaborator across research, planning, implementation, and review—not as a substitute for judgment. My typical workflow is:

1. Research and context: use tools such as Gemini to gather public background information and identify relevant sources.
2. Planning and critique: use ChatGPT to clarify requirements, compare approaches, and challenge assumptions.
3. Implementation and delivery: work with Codex to build, test, document, and refine code and project artifacts.
4. Bilingual review: use DeepSeek and other language tools to support English–Chinese drafting and terminology checks.
5. Human verification: inspect sources, test outputs, correct technical claims, and make the final product and career decisions myself.

Recent applications of this workflow include refining my recruiter-facing portfolio, configuring the custom domain stevewei.ca, improving project documentation, and shaping a career focus around data analytics with an emerging interest in bilingual LLM evaluation.

An end-to-end Toronto rental-data project designed around a practical analytics workflow: public data, Python ETL, SQL modeling, validation, and interactive reporting.

• Interactive demo
• Python, SQL, Power BI-ready outputs, tests, GitHub Actions

An interactive scenario-analysis tool that makes market uncertainty and downside risk visible through simulated price paths, percentiles, VaR, and CVaR.

• Live Streamlit app
• Python package, CLI, tests, CI, Plotly

• Career OS AI Copilot: a local-first Electron prototype for organizing job discovery, approval decisions, application packages, and status tracking through an explicit human–AI collaboration model.
• Aurum Signal Lab: an explainable gold news-event research prototype with event studies, rule-based signal classification, historical analogue retrieval, and a live GitHub Pages dashboard.

• Data and reporting: Python, pandas, SQL, SQLite, data cleaning, visualization, and reproducible workflows
• Quality and delivery: testing, GitHub Actions, clear documentation, and deployed project demos
• AI-assisted delivery: structured research, prompting, implementation, review, and explicit human verification
• Business context: Statistics and Economics education plus previous data-support experience
• Communication: English and Mandarin, with experience communicating in customer-facing and bilingual settings

• Preparing for a Fall 2026 co-op in data, reporting, research, or business operations
• Strengthening practical SQL, Excel, dashboard, and interview skills
• Exploring bilingual LLM evaluation and language-data analysis through a portfolio project
• Finishing projects with clear findings, limitations, and evidence that nontechnical reviewers can understand