I've built and led large-scale data and AI organizations as a CDO, practice leader, and C-suite advisor across financial services, media, retail, and technology. Oxford-trained in AI. Proven at scale. Ready to bring it to a brand, an agency, or a platform.
Whether you're a brand, an agency, or a technology company, a global enterprise or a mid-size challenger, the need is the same. Someone who has actually delivered with data and AI inside a real organization, when the pressure and the politics are unforgiving. I have spent my career in that seat.
What I have learned is that the technology is the easy part. The advantage comes from asking a sharper question than your competitors, then building the capability and the discipline to act on the answer. Most organizations are still buying tools when they should be defining the edge those tools are meant to create.
"The questions we need to be asking aren't 'what AI tool should I use?' They're 'what sustainable competitive advantage can I uniquely achieve in an AI-powered world?' That reframe changes everything."
I sit between the business problem and the data, technology, and creative that solve it. I have been the CDO evaluating the platform, the practice leader carrying the P&L, and the advisor a board actually listens to. I can hold the boardroom conversation and the architecture conversation in the same room.
Most AI initiatives stall inside the organization before the technology ever gets a chance. I have made it work inside skeptical, politically complex companies, designing the teams, governance, and playbooks that move AI from pilot to production and keep it there.
Oxford-trained and field-tested. I build the frameworks that take enterprises from AI ambition to measurable results, and I know the right questions to ask when a vendor's answer doesn't hold up.
Mid-market companies are under pressure to move on AI, and most of what they have tried has stalled. Onbench is an advisory and talent firm for exactly that problem. The advice comes first and costs nothing. When the plan calls for people, Onbench finds senior operators who have done the work before, and stays involved until it delivers.
Built the North American practice from a solo mandate, then absorbed and led an inherited team, reaching 35 people. Full P&L ownership. Served as trusted C-suite advisor on AI and data strategy for major enterprise clients across financial services, CPG, and retail.
Led 100+ person data practice across 8 U.S. cities, $20MM+ P&L. Drove data strategy, analytics, ML, and CRM delivery for Coca-Cola, the U.S. Marine Corps, and other global enterprise accounts.
Primary exec advisor to C-level clients on digital strategy. Led the Google Center of Excellence partnership. Ran product marketing and enablement for 12 specialty AI and data products across a portfolio of 30+ enterprise accounts.
Led cross-functional teams implementing CDP, CRM, and AI platforms for enterprise clients, from strategy and design through delivery. Ran the Spotify retention engagement behind a 30% reduction in monthly active user churn.
Led digital strategy across a 22-brand media portfolio. Modernized the marketing analytics function, replacing manual reporting with attribution, segmentation, and dashboards. 19% revenue increase through data-driven subscription and CRM programs.
Led first mobile app and Asian market expansion. 28% online conversion increase generated $1.7B in potential new assets under management.
Product strategy for a global digital identity and authentication platform serving 14M users and 3B+ daily transactions. $3.6M annual savings through a login, navigation, and password redesign.
Everyone in marketing can name the jobs AI takes. Almost no one can name the jobs it creates. As the production layer collapses, value moves up to the people who translate business outcomes into the systems running execution. That is where the next marketing jobs live, and most of them do not have titles yet.
The Beastie Boys didn't follow the rules. They sampled everything, blended genres that weren't supposed to mix, and built a completely original voice. There's a direct line from their creative philosophy to what the best modern marketing looks like.
The "Garbage Can Model" of organizational decision-making describes how solutions often go looking for problems. Sound familiar? An honest look at how MarTech gets bought, implemented, and why the stack rarely delivers what was promised on the slide deck.
Interactive frameworks and thesis pieces from the working library. Signal is what I use; Fieldnotes is what I think.
AI has moved into marketing faster than the operations underneath it have matured. That gap is where the returns leak out, and it's what this library is about.
Twenty-four questions place your marketing on two axes, operating maturity and AI autonomy, and read the gap between them. No score. A named pattern, priorities, and a first move.
I'm exploring senior data and AI leadership roles where the work is consequential, inside brands, at agencies and holding companies, at the platforms building these tools, and in select fractional and advisory engagements.
Status: Actively exploring · New York, NY · Open to relocation for the right role