While everyone else had polished internships, I needed cash. I took a stockroom job at Target and learned what no internship teaches: how product actually moves, where customers get stuck, what friction actually costs. Turns out it (and a 3.9999 GPA ;)) was exactly what Amazon was looking for as they were building the e-comm business. I got the offer.
Seven years at Amazon across two stints, four years at Apple in between. I launched iPhones, Watches, and accessories across US, Canada, and LATAM (ask me about ops excellence & mitigation planning when leading the largest new product launch in the world); built e-commerce businesses from scratch; took Amazon Australia live; and ran Consumables B2B through the height of COVID (ask me about sourcing hand sanitizer when nobody else could find any). Now I'm back at Amazon externalizing their supply chain so brands outside it can plug into the same infrastructure.
I think in commercial strategy and operational execution. I use AI to make decisions faster; speed matters in business.
I've grown P&Ls, launched categories, and scaled both DTC and B2B. I know what actually moves the number and what just looks busy.
Supply chain, logistics, compliance, speed-to-market. I find the friction in how things move and take it out.
I read the data and I build the thing. Most people are good at one of those; the work lives in the overlap.
Brazil usually launched 8–12 weeks late. To catch the Carnival shopping window I rebuilt the launch flow with supply, logistics, and regulatory; compressed it to one week and captured $xxM in revenue that would have otherwise walked.
Ran the Consumables P&L and a team of seven; built vendor-facing pricing tools that drove $8M in funding year one and erased an annual headcount.
Meltable returns were costing ~$8–10M a year and vendors wouldn't list heat-sensitive SKUs. I sized the global opportunity at $40M, pitched a third-party cold-ship partnership over an in-house build, and launched the program; $5M saved year one, $12–15M by year three, hundreds of new SKUs unlocked.
New albums had no sales history, so release-day OOS sat above 90%. I introduced a pre-order signal into the buy logic; roughly 10% of week-one demand surfaced before launch, unlocked $10–15M in OPS, and became a top negotiation lever with labels.
The fastest way to understand a problem is to build the thing.
I'm in the tools: testing, prototyping, shipping. I got into AI early; certified through AWS, Adobe, and Shopify, active in two AI communities for women, and using it daily to build and think faster. I'm best when the stakes are real and nobody has written the playbook yet.
Strategy, hooks, carousels, captions; I write, design, and ship the post. Built end to end in Adobe Suite, Canva, and Later Analytics; Midjourney joining the stack soon.
Prompts, chains, and systems; not one-offs. I build repeatable AI workflows that run without hand-holding: structured outputs, multi-step logic, automated handoffs. The goal is always the same: remove myself from the loop as fast as possible.
Idea to working prototype in hours, not weeks. I use AI to compress the build-test-learn cycle; spinning up real things fast enough to test with actual users before anyone's written a spec. No playbook required.