I own the operating side of a business unit: budget in, revenue out, the vendors and systems it all moves through, and the reporting leadership plans against. Eight years in operations, seven of them owning the money and the systems, currently a $1.3M budget at one of Florida’s largest public universities. I build the dashboards myself, and the AI automations that took the busywork out.
At FAU’s Career Center I own a $1.3M operating budget: the annual plan, the forecast, multi-year variance across 90+ spend categories, and the reallocation calls that come out of it. I also reconcile 4,000+ transactions a year between TouchNet and Workday to a 0.06% variance, and I own procurement and vendor payments from pre-approval through expense reporting.
The reporting on top of all that is mine too. Six production reports across three workspaces serving two departments and senior leadership, from the data model to workspace access and scheduled refresh. Nobody handed me that environment. I learned Power BI because the spreadsheets stopped answering the question.
What I like most is building the thing that removes the work. An AI automation I put into daily production reads flagged requests and files them as structured tasks with no manual triage: 290 of 311 closed. Given the choice, I would rather fix the process than report on it again next month.
MBA and a B.S. in Business Administration from Lynn University, Lean Six Sigma Green Belt, and I grew up speaking English and Spanish.
Real projects from my current role. Charts are illustrative representations using sample data, not confidential records.
I own the $1.3M annual operating budget: the annual plan, the forecast, multi-year variance across 90+ spend categories, and the reallocation calls that follow. I reconcile 4,000+ transactions a year from TouchNet payments to the Workday GL to a 0.06% variance, and I replaced the manual spreadsheet reporting with a Power BI model that gives leadership live spend-versus-budget visibility.
I track and report revenue for a self-funded events business line against its annual goal: $2.3M gross across 117 events and 8 fiscal years, consolidated into one Power BI benchmark model by event type and customer segment. The operation met or beat its revenue goal in 6 of the past 7 years.
I designed and run the financial and operational tracking for a $1M statewide internship program: a Power BI and Excel data model covering 100+ paid interns, 35 employer partners, and 12 Florida cities, monitoring hours, compensation, and placements. It turned scattered payroll records into one view leadership can act on.
I am not an engineer. I am an operator who got tired of waiting on one. Both of these are running right now.
An AI automation that reads flagged action emails and files them as structured tasks in a Notion tracker with priority, category, status, and owner, with no manual triage. I built it because follow-through was leaking, not because anyone asked for it. It has been running long enough to become the system I actually work from: 290 of 311 captured requests closed over 11 months.
My own sports analytics lab. The flagship project, Cooling Economy, tracked all 104 matches of the 2026 World Cup to test whether the mandatory cooling breaks changed match play, and modeled what the break airtime was worth in US ad money. I built the pipeline end to end: ESPN and weather APIs into SQLite, refreshed twice daily by GitHub Actions, feeding a bilingual dashboard where every figure is labeled fact, estimate, or assumption. The verdict went against the interesting answer, and it is published anyway.
Budgets, revenue, reporting, and the automation underneath. If you are working on any of it, I am glad to compare notes.