About
What I do.
I build the systems a product organization runs on: how it decides what to build, scales execution, and learns whether it worked.
Throughout my career, I've led products from discovery through scale, creating solutions that deliver lasting customer and business value. But underneath all of that product work, one constant remains: the operating models and capabilities a team uses to operate effectively. When those systems are strong, an organization compounds what it knows and executes consistently. When they're missing, it keeps re-solving the same problems.
The sharpest version of this is experimentation and measurement. I build both the products that help organizations validate growth opportunities and the programs that embed continuous learning into how teams build. A test is only as valuable as an organization's ability to act on and remember it. The same logic applies anywhere team operations become the bottleneck, whether that's strategy, intake, prioritization, or planning cadence.
That is why this work spans design, engineering, data, and business. It isn't about wearing four different hats; you simply can't build the system that connects those functions without being fluent in all of them. That breadth is how I do the job, not the job itself.
The sauce
I approach product through four interconnected lenses: design, engineering, data, and business. Working across these disciplines allows me to build products that deliver measurable outcomes while improving the product organizations that build them.
- Design
- Engineering
- Data
- Business
What I can help with
How I work
I've learned the fastest way to build the wrong thing is to assume. Curiosity uncovers opportunities that assumptions often miss.
Whether it's a feature, a roadmap, or an organization, I like understanding the whole system before changing one part of it. So -as covered- I may ask questions
One of the most valuable things a product leader can do is create enough clarity that everyone else can focus on building instead of interpreting.
My engineering background taught me that every system has a constraint or a few. I instinctively look for it before optimizing everything else.
I don't expect every decision to be perfect. I care more about creating fast feedback loops that help us learn what works.
I enjoy working at the intersection of design, engineering, data, and business because that's where the best product decisions tend to happen and many questions get answered.
Whether it's a product strategy or an operating model, I enjoy taking something that feels complicated and making it easier to understand, discuss, and execute.
I've learnt that a solution can create more problems and while shipping is important, so is thinking about what the next team, feature, or decision will inherit.
The product matters, but so do the environment that produces it and the people expected to adopt it. Products are a reflection of the organizations that build them.
The kinds of problems without obvious owners, clear answers, or well-defined paths are usually the ones I find most rewarding.
I work best embedded directly alongside technical and non-technical operational partners - sitting in the trenches to observe daily workflow friction, prototype immediate fixes, and translate hands-on needs into scalable solutions.
Capabilities
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Build Products
Product strategy & vision · Discovery & user research · Roadmaps & prioritization · Requirements · Delivery and go-to-market · Monetization & commercial model · AI product strategy & development · LLM-assisted prototyping · Design-to-engineering fluency · Front-end development · Product design
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Build Product Operating Systems
Product operations · Operating model design · Portfolio & delivery governance · Planning cadences (QBRs, offsites) · Capacity management · Process design & change management · Cross-regional orchestration · Vendor & partner management · AI adoption & enablement
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Measure Impact
Experimentation platforms · Experiment design & statistical rigor · A/B testing & Geo Lift · Measurement strategy & governance · Test-and-learn programs · Personalization & optimization
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Turn Data Into Decisions
Data strategy & governance · Analytics & reporting · Dashboards & visualization · Decision frameworks
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Leadership & Management
Cross-functional leadership · Stakeholder management · Executive communication & storytelling · Talent development & mentorship
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AI Prototyping & Developer Stack
Claude · OpenAI · Gemini · Cloudflare · Cursor · GitHub · Local AI Workflows ("Vibe Coding")
* A representative sample, not an exhaustive list.
Selected experience
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Sr. Director, Product - Data, Media & Experimentation
Monks
Strategy, governance, and commercialization for the media product portfolio; led the ground-up build of its flagship experimentation & measurement platform.
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Lead Product Manager - Experimentation
Best Buy
Built the in-house experimentation platform that replaced third-party tooling across a high-traffic e-commerce ecosystem, and embedded an always-on test-and-learn program.
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Product Manager - Audience Insights & Analytics
McKinsey & Co
Led a 10+ person team building self-serve analytics and reporting products for stakeholders across business units globally.
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Product Manager - Data Acquisition & Ops
22Squared
Established the data-acquisition practice and operating model from scratch, and moved the data & analytics org to Agile.
Earlier: measurement and activation at AutoNation, product-marketing design at Assurant, and a first career in engineering and design. Full history on LinkedIn →
BS Industrial & Mechanical Engineering · MS Petroleum Engineering · BFA Web Design & Interactive Media
How I write
I develop the ideas, arguments, and examples in my writing from my own experience and research. I use AI as an editing partner to question the structure, clarify passages, or tighten language. I review and revise every piece, and the final judgment about what to say and how to say it is mine.