Most data analysts think in queries. I think in business outcomes first — then figure out what query gets us there.
That's the economist in me. And it's why the work tends to stick.
I have a degree in Business Economics with a minor in Data Analysis. I spent 5 years at a B2B financial services company — starting as the data and operations lead for their portfolio of 400+ corporate clients, building automated pipelines that eliminated multi-day reconciliation meetings, cutting reconciliation errors by 99%.
From there, I was promoted to manage my own portfolio of 20-30 corporate clients — making the daily call on pricing, comparing market rates against our desk's position. Those decisions generated $1.5M+ in net profit — and they're why I never look at a dataset without asking what it means for the business, not just what it says.
Now I work independently with early-stage startups in the US — building the data layer that lets them scale without a full in-house team.
100% remote. Available ET hours. I work from wherever I am — no office politics, no overhead, full focus on your project.
I prioritize documentation and clean handoffs — so your team can understand, maintain, and build on what I deliver.
Every engagement is clearly scoped with defined deliverables and timelines. You know what you're getting and when it's done — before we start.
Book a 30-minute discovery call. We'll figure out exactly what you need — and whether I'm the right person to build it.