I’m at my best when the answer isn’t obvious: when user experience, system behavior, and operational reality don’t quite line up. I investigate the gap, find the signal, and turn it into clearer decisions, stronger systems, and better ways of working.
A change that looked successful in one part of the product created failures downstream across screening, billing, and customer experience. I traced the mismatch across systems and brought the full picture to Product.
When screening results appeared stalled, I connected customer frustration with the compliance and data-validation processes happening behind the scenes, helping translate that reality into clearer in-product messaging.
Across partner-integrated products, I’ve reconstructed what happened by following evidence across internal systems, external partners, customer configurations, data, and human accounts.
Selected work to come.
My work has spanned launch readiness, communications, onboarding and configuration, pricing and billing changes, partner migrations, regulatory updates, product sunsets, enablement, exception handling, post-launch investigation, and feedback back into Product.
I haven’t owned the roadmap. I’ve worked on the parts that determine whether a product change can actually be understood, adopted, supported, and improved as it moves from an idea into the real world.
High-value inventory demanded exact reconciliation across physical assets, records, and client expectations. I built my reputation on finding discrepancies, restoring accuracy, and keeping complex operations controlled.
~$8.5M in inventory · ~11,000 pieces · sustained 100% inventory accuracy · $1.85M in incremental e-commerce revenue
Customer experience, partner behavior, regulation, and product logic rarely lived in one place. I reconstructed the full picture and translated it into something Product, Engineering, Operations, or the customer could act on.
Today I apply the same instinct to complex AI product behavior: evaluating whether outputs are grounded, contextually appropriate, useful, consistent, and behaving as intended.
~96%
customer satisfaction across five years
That included a full year of monthly 100% scores while working in complex, regulated, dependency-heavy environments.
But the pattern isn’t only customer-facing. I’ve repeatedly been the person teams rely on for context, continuity, deep product knowledge, and keeping information — and people — connected.
I started working in Melbourne, Australia, after walking into a flagship retailer I loved with a cover letter, even though there wasn’t an advertised opening. They hired me.
Starting there, and later continuing my career in the U.S., taught me something I still rely on: context matters. Different environments have different rules, expectations, language, and ways of working.
I learned early to observe first, understand the system I’m in, and then figure out where I can make it work better.
The industries have changed dramatically. That instinct hasn’t.
I separate the actual problem from the symptoms surrounding it.
If something keeps happening, I’m interested in the structure producing it.
A technically correct answer can still be wrong for the user, the workflow, or the situation.
Whether it’s a product question, an operational knot, or a system that just isn’t behaving the way anyone expected, I’m always interested in the problem underneath it.