Finance operator. Systems builder. Decision partner.

In many corporate finance teams, analysts spend up to eighty percent of their monthly close assembling spreadsheets: extracting raw general ledger rows by hand, stitching disparate workbooks together, chasing unmapped cost centers, and manually pasting totals into static presentation decks.

By the time the numbers reach executive leadership, the team is exhausted by the mechanics of assembly. Little energy remains for the critical work that actually drives business value: rigorous variance explanation, risk challenge, scenario modeling, and capital allocation decisions.

My work is focused on reversing that equation. By treating financial modeling and reporting with the discipline of software engineering—designing reproducible SQL extraction pipelines, defensive validation layers in Python and VBA, and standardized Power BI semantic models—we compress multi-day manual reporting marathons into reliable, same-day delivery.

The engineering layer matters because it creates time, consistency, and institutional trust. But the technical pipeline is always subordinate to commercial reality: numbers require context, judgment, and clear framing to enable executive action. I work where those two domains intersect.