About me
I’m Chen — an AI-focused developer and data professional with a background in finance, telecom operator analytics, local services and content safety. I started out in data analysis and metric modeling (Python, SQL, star-schema and wide-table design) supporting product and business decisions, then gradually moved into building web products of my own.
On this site you’ll find both my finished work and the thinking behind it: a keyword-research pipeline that decides what to ship, a content-led editorial site built directly from that research, a calculator toolkit, a small browser-game hub, an experimental “don’t click” site, a memorial project, an emoji code tool, and a public-records-backed civic transparency project. None of these are toy demos — each one is shipped, domain-registered, and indexed.
I try to operate with strong E-E-A-T: real-world experience, transparent methodology, technical depth, and a track record of projects you can click into and verify.
Approximate years and where I focused — the path from data to shipped product.
Shipping niche sites with research front-ends
Running a Google Trends + keyword-research pipeline that identifies long-term SEO opportunities, then building the editorial site directly from the data (TechPulse is the latest build). Adding a public-records-based civic project to the same workflow.
Web tooling, content, and headless CMS
Shipped Calculate Central (calculator toolkit), GemGuidePro (gemstone content platform on Next.js + Sanity + Cloudflare), PuzzleZone (HTML5 game hub), Emojitik (TikTok emoji code tool), and the Digital Epitaphs project.
Data analytics and metric systems at scale
Worked across finance (risk, credit, transaction analysis), telecom (user lifecycle, plan strategy), local services (to-store / to-home merchant analytics) and content safety (policy + model performance review). Most of my time went into metric design, wide-table modeling, and translating business questions into measurable analysis.
Four rules I try to keep for every project, big or small.
Data drives the decision
Before building, I check whether the opportunity is real — search volume, keyword difficulty, intent mix, domain fit. If the data doesn’t support it, I walk away.
Ship the smallest useful thing
One project per week, end-to-end. The smaller the scope, the faster the feedback loop, the better the next iteration.
Human review as a hard gate
AI assists drafting and editing. Every claim carries a source. No AI-generated quotes, no auto-publish, no silent edits.
Show the work
Every claim, dataset and decision is verifiable — links to primary sources, public records, code, or the change log. No black boxes.
What’s next
I’m currently looking to spend more time on the keyword-research pipeline and content-as-code workflows, and to ship one more niche editorial site in 2026. If you’re building something adjacent (research pipelines, content-led sites, civic transparency tooling), I’d love to compare notes.