About
I'm a Data Scientist and AI engineer with a background in accounting and operations analysis — a blend of financial expertise, technical depth, and applied AI experience focused on solving real business problems. The path from certified accountant to data scientist to AI systems builder shaped how I work: with business acumen, analytical capabilities, and hands-on skill at building automated, agent-driven workflows.
What I'm doing now
- Building Internal operations platform at Day & Night Solar — finance system, QuickBooks automation, reconciliation engine, document intelligence, AI-integrated workflows.
- Shipping Cinemetrics — full-stack SavvyCoders capstone (Node · Express · MongoDB · REST APIs), deployed end-to-end.
- Exploring Multi-agent orchestration · local LLMs (Ollama) · document forensics · Postgres migration · reproducible finance pipelines.
- Open to Data Analyst, Analytics Engineer, Data Scientist, Junior Software Engineer, or Finance/Operations roles where accounting, data, and code intersect.
The path here
What began as pattern-finding in financial data has grown into building full data and AI systems. I spent a decade in accounting — general ledger, reconciliations, fixed assets, AP/AR across enterprise ERPs at NTT, Curtiss-Wright, Robert Half, and Walmart eCommerce. Before that, I ran my own service business for 13 years: full P&L, payroll, state compliance, a team of six, and 10–12% YoY revenue growth through digital marketing.
The through-line has always been reconciling high-volume financial data across messy source systems. What changed is the tools — first Excel, then Python, then ML models from the TripleTen data science program (16 end-to-end projects: churn, pricing, forecasting, NLP, a CNN regression), and now full-stack from SavvyCoders. Today I design AI-assisted workflows and agent-based systems on Claude Code, build domain-specific databases and tooling, and work at the intersection of finance, operations, and automation.
My current focus: using AI orchestration and data engineering to streamline complex back-office operations — combining traditional analytics with agent-based systems to deliver results that would otherwise require much larger teams.
How I work
- Build once, reuse forever. Prefer automation over repetition.
- Think in systems, not tasks — then make the system legible to the next person.
- A result you can't explain isn't a result yet. Write it down.
- CPA-grade mindset: controls, audit trails, and reversible operations by default.
Skills
Core — used regularly, confident Working — shipped with it, still growing Exploring — actively learning
Programming & AI
Where I spend most of my build time right now.
Data & Engineering
Turning messy source systems into something you can actually query.
Machine Learning
Classical ML where I've shipped measurable results, plus what I'm building toward.
Full-Stack Web
The SavvyCoders stack — built a real capstone in it.
Finance & Enterprise Systems
The foundation — still shapes how I think about controls, audit trails, and data integrity.
Business Domains
Where my work has made real decisions.