Turning ambiguous problems into systems

Career narrative

The thread across thirteen years is the same one every time: take a problem nobody has fully framed yet, find the structure inside it, and 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 widening the aperture from a channel to a funnel to the whole business. At Keypath Education I've spent over a decade moving through that arc: media buyer, digital media specialist, marketing manager, marketing and CX manager, and now CX manager for the Australian portfolio, working across admissions, marketing, paid media and data. 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, aligning stakeholders across four functions before touching 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, find the evidence, build something that holds up once I'm not the one holding it together.