I translate context from dirty data to build products people love.
Technical Acumen+Applied Context=AI Success
Every business is sitting on data they don’t know how to act on. From capturing the Coca-Cola legal team’s compliance case-management requirements, addressing NBA League Pass’s usability nightmare, to quantifying a $42M user story at FanDuel, my methods as a historian with data science training are proven. Now, I’m empowered with AI tools.
The perspective
- Historiography, appliedWho wrote it, when, and with what interest. Authority is assigned, never assumed.
- Mixed-method researchSurveys and benchmarks on one side, interviews and agent testimony on the other. Neither is evidence alone.
- SDLC & delivery governanceStage gates, readiness reviews, decision registers. Twelve years shipping where a bad release is expensive.
- Full-stack, product-ledGeorgia Tech Data Science & Analytics on top of ten years in product. What I used to specify and hand off, I now build.
Selected work
See some of my work.
Four arguments, each one married to something I built and can show you. Every figure on a tile is taken from the page it links to.
01 · Red Eagle
Context Is [Key]
In 2012 I published a paper on the Creek leader the newspapers called Red Eagle. Then I left history and spent fourteen years using analysis skills to help build products people love. Now, I’ve picked up that history paper again and leverage AI to breathe new life into the old project. Getting a content generation pipeline to clear rigorous historical accuracy requirements illustrates the governance rigor required to develop AI-powered products & solutions. Take a look!
221 beats · 55 drawn · 57 held until the right people are consulted
The story structure the design is built on
Four tiers, skeleton to understanding · the design follows the story
02 · Deep Dives
“The app always thinks I’m on the other side of the river!”
Issues at legal-to-legal state boundaries cascaded into real, measurable losses to product loyalty and revenue. Nobody owned the location check, so a poor Login score was explained away for years as the cost of doing business, until the detractors’ own support records were read against their scores and the cost of doing nothing was priced.
57% of users failed a location check inside a legal state · −13% loyalty near the border · est. −$42M a year · full figures in the deep dive
One stage of the map · the artifact the deep dive is built on
Score, issues, impact and the opportunity, per stage
Tap a number, or let it run Swipe, or tap a number
Reads asPrincipal Product Researcher · Lead Customer Experience Strategist · Senior Digital Product Strategist · Product Discovery Lead · AI Experience Researcher
How the method was built
Career history, compressed.
Product Manager, SaaS → Voice of Customer Strategy Lead → Independent AI Product Consultant
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Independent
AI Product Consultant Now running AI research pipelines end to end, solo. Red Eagle is the proof of method.Building generative research programs where AI runs the whole SDLC as one resource: eight defined roles, gated stages, a single operator. Dates and detail in the résumé.
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FanDuel
Sr. Manager → VoC Strategy Lead Built VoC for Racing, found a location defect in the priority score, and led the company-wide deep dive it triggered.Racing product partner for Customer Insights from 2021, where the VoC program was mine to build. The competitive benchmark belonged to UX Research and they ran it; what I built was the priority score across both, matching survey detractors to their own behavior. That is where location surfaced, and it was not a Racing problem. Promoted to Lead VoC Strategist on the scale of it, then led the deep dive across racing, sportsbook, casino and fantasy with a dedicated analyst and stakeholders from each: GPS, churn, screen replays, agent and VIP handler interviews, financial modeling. The deep dive.
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WarnerMedia · NBA Digital
Manager, Customer Satisfaction Owned CX across a 16-platform streaming estate: 370k+ subscribers, 4×+ growth, BBB rating D to A.Product ownership of live services and support across the whole streaming estate, and the discovery that users, customers and fans are three different populations. Defined the taxonomy and KPI framework every downstream insight ran on, reported directly to NBA executive leadership.
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Coca-Cola
Business Analyst, Ethics & Compliance Turned requirements-gathering into a documentation discipline stakeholders actually trusted.Requirements gathered in detail from business partners so delivery matched what they actually needed. Where documentation stopped being a chore and became a skill.
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IHG
Project Coordinator Coordinated a global reservation-systems rollout across 20+ developers: change that has to land, not just demo.Assembling the resources and the plan behind a real change, which has to land across an organization, not in a demo. Global reservation systems, 20+ developers, deployment at scale.
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Siteminis
Account Manager → Product Manager Learned what makes a product worth buying by sitting with the prospects deciding not to buy it.Sitting with prospects on what would make the product worth buying set the direction for everything after: you cannot justify a product improvement without the customer evidence behind it.
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B.A. History
Auburn University Trained to weigh conflicting testimony before trusting it, published research still the standard I hold data to.Historiography is training in reading against your own bias: criticize the context of a source before you credit its content. Published on Weatherford and the end of the Creek frontier in the International Journal of Interdisciplinary Social Sciences.
Next
Tell me what you're trying to prove.
Leaders bring me friction to quantify, roadmaps to sharpen, and customer sentiment that has to drive action. A role, an engagement, or one hard problem: tell me what you're trying to prove and I'll tell you what it would take.
Currently advising Atlanta-area businesses on knowledge capture: getting operating knowledge out of people's heads and into a structure a system can use, then judging where generative automation earns its cost and where it doesn't.