Turning ambiguous problems into systems

Career narrative

The thread across thirteen years is the same one every time: find the structure inside a problem nobody has fully framed yet, then build something that keeps running after I step back. The titles changed a lot more than the underlying work did.

I started in digital media buying, running paid search and paid social campaigns and learning to read a dashboard for the decision hiding inside it. That pulled me into marketing, then into leading a marketing team, then into customer experience. Each move widened the aperture, from a channel to a funnel to the whole business. I spent over a decade moving through that arc, first at Plattform Education, which became Keypath Education, and then at Keypath: media buyer, digital media specialist, marketing manager, marketing and CX manager, and finally CX manager for the Australian portfolio. Every step added a layer of the business I had to understand well enough to explain simply to the people making decisions in it.

The constant underneath the titles is the same instinct: simplify complex strategy so people can actually act on it, and back decisions with evidence instead of hearsay. That instinct is what's pulling me toward AI now. I've led the evidence work behind a lead-scoring model that replaces fixed tiers with a proper probability score, and I aligned stakeholders across four functions before anyone touched a line of the build. I've also run an end-to-end pilot on AI-driven SMS engagement, built on a randomised holdout so the result means something rather than something that just feels right.

None of that is a pivot away from what came before. It's the same operating system, aimed at harder problems: frame it properly and find the evidence, so what I build holds up once I'm not the one holding it together.