I’ve spent my career working across startups and large organisations, taking ideas from early exploration through to production. My work has covered everything from recommendation systems and predictive models to computer vision and optimisation problems. But more importantly, it’s been focused on making these systems  deliver value in real-world settings.

Along the way, I’ve led teams ranging from small, high-impact data science groups to larger cross-functional teams in enterprise environments, helping them scale solutions and navigate trade-offs I enjoy working at the intersection of technical depth and practical decision-making -- scaling systems and understanding downstream effects of trade-offs.

This blog is where I share what I’ve learned building AI and ML systems in practice: what works, what doesn’t, and where teams tend to get stuck. It’s aimed at people trying to make these initiatives succeed, technically and strategically. 

I’m also still closely connected to Academia, with 14 publications from my MSc and PhD work, and ongoing involvement in reviewing research in statistics and machine learning. 

Outside of work, I’m a (tired) parent of three, an ocean lover with too many surfboards, and a keen photographer.