I'm a finance graduate student with experience in business operations data analysis. I use AI-assisted development to build practical tools that turn business data into clear, actionable insights.
My focus is on understanding the business question first, then combining data analysis, visualization, and lightweight automation to deliver a reproducible solution.
- Business analytics and performance measurement
- Data analysis and visualization
- AI-assisted tools and workflow automation
- Operations problem-solving
An interactive dashboard for multi-store performance analysis. It validates multi-period CSV data, derives core operating metrics, aggregates results by region, city, and supervisor, and supports filtering, ranking, and drill-down.
- Repository
- Live Demo
- Python, HTML/CSS/JavaScript, synthetic sample data
A business-district and competitor analysis workbench built on synthetic store data. It supports district health scoring, competitor pressure, marketplace fee and promotion comparisons, multi-district benchmarking, and rule-based diagnostic recommendations.
- Repository
- Live Demo
- JavaScript, Python, Cloudflare Pages, synthetic sample data
A Python CLI workflow that compares planned business hours with observed online periods to identify abnormal closure intervals, estimate simulated impact, and generate Excel, Markdown, and JSON reports.
- Repository
- Example outputs
- Python, openpyxl, synthetic sample data
All public projects use synthetic data. They demonstrate analytics and automation workflows, not real business results.