Hello, I'm
I transform enterprises through AI platforms that executives bet hundreds of millions on.
Senior Director of Product at Walmart. I've transformed ambiguous enterprise problems into production AI systems that drive $600M+ in business impact. I scaled product teams from 4 to 10 PMs while coordinating 60+ technical personnel. Former Navy Nuclear Officer. Duke MBA.
I learned leadership on a nuclear submarine, earned technical depth through a CS degree, and refined strategic thinking at Duke.
I don't just build products—I drive organizational transformation. When I built Walmart's forecasting platform, I didn't just ship software. I changed how Finance and Merchandising collaborate, replaced manual Excel processes with ML-driven planning, and got 6 business units to adopt a shared system. That's change management at $650B scale.
I think in systems, not features. When I walked into Walmart's forecasting problem, I didn't see a dashboard gap—I saw Finance and Merchandising operating on different truths. Built a platform that unified them. When ML models shipped with 30% accuracy gains, I didn't celebrate early—I validated coverage expansion before scaling.
I operate at the intersection where technical credibility meets executive influence. I've presented quarterly roadmaps to C-suite stakeholders, built consensus across SVP leaders for $100M+ initiatives, and secured multi-year platform investments by translating ML capabilities into P&L impact.
I'm most valuable when the problem is ambiguous, the stakes are high, and success requires both building the right team and building the right product.
I've operated in environments where a 25 basis point improvement means $200M, and where getting a product to production requires aligning C-suite stakeholders across Finance, Merchandising, and Supply Chain.
Coordinated 60+ technical personnel while building consensus across SVP leaders for $100M+ initiatives. I present quarterly to C-suite and translate ML capabilities into P&L impact.
Built systems designed for enterprise adoption—not one-off solutions. Secured multi-year platform investments by demonstrating scalability from pilot to production across multiple business units.
Drove organizational transformation by replacing legacy Excel-based processes with unified ML-driven planning systems. Adoption isn't an afterthought—it's core to the product strategy.
The Problem: Finance and Merchandising ran on separate forecasting systems. Finance had Excel models. Merchandising had legacy planning tools. Nobody had a single source of truth for a $650B business.
What I Did: Built Walmart's first unified ML forecasting platform—replacing fragmented Excel-based workflows with a single source of truth. Driver-based models, demand forecasting, and Gen AI explainability. This wasn't just a product launch—it was organizational transformation across a $650B business.
Impact: Targeting 25 bps margin forecast accuracy improvement ($200M+ annual) and $400M incremental sales through reduced stockouts. Scaled across 6 Merchandising business units. Presented quarterly to C-suite.
The Problem: ML forecasting was proving value in pilots, but the business hadn't committed to platform-level investment. Without multi-year funding, we'd stay stuck in proof-of-concept mode.
What I Did: Built a business case showing P&L impact, not just model accuracy. Demonstrated how forecast improvements translated to margin gains and inventory optimization. Coordinated SVP stakeholders across Finance, Merchandising, and Supply Chain to align on vision.
Impact: Secured multi-year investment that positioned the platform as Walmart's enterprise forecasting engine. Expanded from pilot to production across labor, capacity, and financial planning workstreams.
The Problem: Assortment optimization was stuck in competing priorities across business units. Each SVP had different goals. No one agreed on how to measure success or prioritize rollout.
What I Did: Aligned stakeholders on a shared metric: sales lift. Demonstrated $100M+ one-year impact through ML-enabled store-item optimization. Coordinated 60+ technical personnel to deliver a 2% sales lift in initial rollout.
Impact: Accelerated assortment transformation with $1B+ potential annual revenue impact. Partnered with Applied AI to increase model accuracy by 30% and expand business coverage 4x.
Zero-error nuclear operations on strategic deterrent patrols. Entrusted with critical national security mission during global tension.
Master of Business Administration
Decision Sciences
Fuqua Class of 1987 Scholarship | Dean's List | GPA 3.86
Design Thinking Bootcamp
Human-Centered Design
Bachelor of Science
Computer Science
Division I Basketball | MIT Draper Lab Internship
Building product visions that align technical capabilities with business objectives at enterprise scale.
Translating machine learning capabilities into production systems that drive measurable business value.
Building alignment across engineering, data science, design, and business stakeholders.
Using analytics and experimentation to validate hypotheses and drive continuous improvement.
I'm most energized by ambiguous 0→1 problems at enterprise scale—where technical credibility, executive influence, and operational discipline converge.
I'm drawn to roles where AI/ML strategy directly shapes capital allocation, and where building the right team matters as much as building the right product. The best problems are the ones where nobody's sure it can be done, the stakes justify the investment, and success requires both shipping code and shipping organizational change.
I've built platforms that inform billions in decisions at Walmart. Next, I want to lead product at a company where AI/ML strategy shapes competitive advantage—whether that's as VP/Chief Product Officer driving transformation at scale, or as a founding product leader at a company betting its future on AI.