Business analysis · Applied mathematics & philosophy

I turn ambiguous business problems into requirements and decisions people can check.

I’m an IT business analyst intern on an industrial B2B platform used by staff and dealers. Drawing on applied mathematics and philosophy, I translate business processes into requirements, frame the trade-offs a decision depends on and check results against operational needs. The case studies below are simplified, independent versions of problems related to that work, built with fictional data.

See the workEmailGitHub

A decision, with its reasoning.

A decision sheet for the question “What should ship now?”, using the same tight containers and stock with only the shortage cost changed. Plan A opens only the large container, which is full by volume with 112 units: lower container cost, 112 of 309 units ship and 197 are short; optimal at the original shortage cost. Plan B opens both containers, both full by volume, with 117 and 13 units: less unmet demand, 130 of 309 units ship and 179 are short; optimal when shortages cost four times more. Three lenses on the same decision: business context asks what a unit of unmet demand is worth; the model treats capacity as a hard limit; the assumption is that the shortage cost is a judgment, not a fact. Conclusion: the preferred plan depends on the shortage cost.
From the shipping case study’s fictional scenarios: the same containers and stock, with only the shortage cost changed. See the case study →

Experience

Where these problems come from

IT Business Analyst Intern · Heli America Inc. · August 2026–present

I work with a software lead on an industrial B2B business platform used by staff and dealers. My responsibilities include translating business processes into requirements, coordinating data-quality reviews, directing AI-assisted implementation work and checking results against operational needs.

Selected case studies

Four problems. A consistent way of reasoning.

Each case study is a simplified, independent version of a problem related to my work, built with fictional data or a hypothetical scenario, so the requirements, assumptions and reasoning are visible. Each comes with a short write-up and code you can run on a laptop.

How I think

Structure the problem. Examine the assumptions. Explain the decision.

Each card pairs a reasoning habit with an example from one of the case studies. The other four habits are on the How I Think page.

All eight principles in How I Think

About

I translate how a business runs into requirements, coordinate data-quality reviews and check results against what the business actually needs.

My background is in applied mathematics and philosophy. Mathematics gives me ways to model a problem; philosophy makes me ask what would justify the answer.

Tools and methods in these projects

  • Python
  • PuLP/CBC
  • Integer optimization
  • Independent feasibility checks
  • Domain modeling
  • Mermaid
  • Architecture decision records
  • Python standard-library checks
  • Python/pandas
  • Streamlit
  • Altair
  • Ordered session funnels
  • CSV ETL
  • Deterministic reference mapping
  • pytest

AI tools used to build them

  • ChatGPT
  • Claude
  • Codex
  • Claude Code

Contact

Email
hyang26@alumni.wfu.edu
GitHub
github.com/h-yang-26