I turn complex financial and operational data into clear decisions, using SQL, Python, Power BI, Tableau, and seven years of fintech context behind every chart.
For more than seven years I worked inside fintech operations at a payment processor, helping a portfolio of 12,000+ merchants keep running: analyzing their transactional, billing, and settlement data across $50M+ in monthly volume, resolving discrepancies, and building the reports leadership relied on to make decisions.
That work made me want to understand the tools and processes behind it all more deeply, so I went back to school for a B.S. in Information Technology, expanding my technical foundation and learning how the systems I had worked with actually fit together.
Along the way I realized my real passion was in the data itself. I leaned all the way in, completing an intensive Data Analytics Bootcamp, building real-world projects in SQL, Python, Tableau, and Power BI, and preparing to begin an M.S. in Data Analytics. I continue sharpening my ability to turn messy data into clear decisions, a craft I plan to keep enriching for a long time.
The skills I use to collect, clean, analyze, and visualize data, and a toolkit I am always expanding.
Extracting, filtering, and aggregating data, from simple lookups to multi-table joins and complex subqueries.
Data cleaning, transformation, and analysis, from formulas and pivot tables to automated Power Query workflows.
Interactive dashboards and reports with calculated measures, data modeling, and visual storytelling.
Interactive dashboards, KPI tracking, and data storytelling that surface outliers at a glance.
Data manipulation and visualization through real projects using industry-standard libraries.
Shipping full-stack side projects, like a production platform on Supabase/PostgreSQL with REST APIs and an LLM chatbot.
Each project built around a real business question and real data.
Self-directed builds driven by curiosity rather than a syllabus: larger, open-ended, and engineered end to end. First up: AZIMUTH, in active development.
How does any launch vehicle really stand against the whole market?
A provider-agnostic BI platform that models the global orbital launch market and benchmarks any vehicle against the field. Built from scratch on a Databricks lakehouse, in the open, with a running build log.
Follow the build → GitHub ↗Personal projects rooted in my studies. Each one takes a dataset, brief, or concept from my IT degree or data bootcamp and carries it further with real data and my own analysis.
Where do hospital bed-days actually go, and how concentrated is the burden?
Analyzed 101,766 hospital encounters and found the 21% of stays lasting 7+ days consumed 43.5% of all bed-days, using CTEs, window functions, and multi-table JOINs.
Read the case study →Playing data analyst for the Boston Celtics: shooting, playmaking, roster age, and winning without Tatum.
Four front-office questions answered with 2025-26 data: four related data sources, a before-and-after on shooting efficiency methodology, and an interactive story that drills from conference down to individual players.
Read the case study → Tableau ↗Seven case studies across SQL, Python, R, Tableau, and Excel, each built on real data.
Verified credentials across cloud, data, security, and IT. Click any badge to verify.
Plus four stacked CompTIA specialist certifications: IT Operations Specialist, Secure Infrastructure Specialist, Cloud Admin Professional, and Secure Cloud Professional.
The things I enjoy most when I'm not working.
I love this sport for its blend of speed, strategy, and reading your opponent in real time. Proud registered member of USA Fencing.
Movies of every era, from brand-new releases to old classics. My all-time favorites: Top Gun and Drive.
Spaceships, space exploration, and honestly anything with the word "space" in it. It even sparked my AZIMUTH launch-analytics project.
I stepped out of the corporate world for a while to witness my first daughter's earliest milestones. I wouldn't trade it for anything.
Based in Seattle, always happy to talk data, tech, and building things. If you want to trade notes, collaborate, or just say hi, my inbox is open.