I build and run the systems that keep an operation working.

The bank had to prove to its regulators which of thousands of applications carried known security vulnerabilities, including Apache Struts, the flaw behind the Equifax breach. Several teams had tried to get a reliable count and failed. Without it, the bank could not report progress to the OCC or tell owners what to fix.

I built the SSIS and SQL pipelines that pulled data from the security scanning platforms into one governed picture that met the auditors' bar. On the Struts problem, I pulled the team together, mapped where every past attempt broke down, and worked across the scanning groups to agree on what actually counted as embedded. Then I built the reporting that tracked remediation across the org every week, and the Tableau dashboards the risk teams ran on.

A working enterprise-wide scan and a weekly report leadership could take to the regulators. A problem that had stalled for years got unstuck, mostly because I built the cross-team relationships to get everyone on one definition. More than 20 risk teams used the reporting I built, and I automated over 2,800 hours of manual work in my first year.

I wanted a job running mobile user acquisition, didn't get it, so I built the business myself. We ran ad campaigns for iOS and Android apps. Running them meant eight hours a day of logging into ad systems, matching offers by country, and babysitting them.

I hired and ran a team of four, and I built a Python automation that hit the ad-network APIs directly, found the offers that fit our traffic, launched them, and checked every one before it ran. It erased the eight-hour grind, and I licensed it to other companies as a product.

Grew it to $1.8M over four years, drove more than a million users, and turned my own internal tool into revenue. It was the first time I ran a team and a P&L, and I did both.

Pricing six rental units by hand was a guess. It missed booking pace and demand, so some months filled below market and slow dates were caught too late.

I built a system that reprices every night and the moment a booking or cancellation hits. The math decides the move and an AI layer reads the signals and explains it in plain language. Nothing changes a live price without my approval, and it learns from every booking. It runs on Postgres and serverless functions and pushes rates to Airbnb, VRBO, and Booking in seconds.

Running about 40 percent ahead of our best year ever, with four months still to go, and weekly pricing work went to zero. The point for a county: I know how to bring AI and automation into a real operation safely, with guardrails and a person approving the calls, not a black box.

The booking platforms take about 15 percent and own the guest. Direct bookings leaked money because we sent payment links after confirming and guests would not pay, and some showed up having never paid.

I built a pay-to-book platform on Square where the guest pays before the reservation exists. On my approval it captures payment, blocks the dates across every channel, and sends a branded confirmation, and it runs the whole booking lifecycle on a live KPI dashboard.

246 bookings at 100 percent payment compliance, the unpaid stays gone, and about $13K in platform fees reclaimed. It is now my second-biggest booking channel.