From the business question
to the working system.

Useful strategy work makes the economics of a business visible: price, demand, capacity, customer value, and the tradeoffs behind the next move.

• Pricing models and scenario analysis
• Revenue forecasts, operating plans, and P&L models
• Lifetime value, retention, and acquisition economics
• Executive analytics reviews and decision support

The result: a model you can use, assumptions you can inspect, and a clear account of what the numbers mean.

An AI idea becomes useful when it fits the people, data, and decisions around it. I work alongside the team to map the process, build the integration, and carry it through to daily use. This is forward-deployed engineering: hands-on implementation inside the operating context.

• Process mapping: find bottlenecks, repeated decisions, and manual handoffs
• Claude and OpenAI API integrations connected to business data
• Workflow automation with human review and clear exception handling
• Evaluation against real examples, documentation, and team handoff

The result: a working workflow with agreed checks for quality, useful output, and a clear owner when something needs attention.

Technology is the practical layer underneath the strategy and the AI work. I build the pipelines, APIs, internal tools, websites, cloud systems, and integrations that let a business stop waiting on manual glue.

• API integrations, SQL models, and production data pipelines
• Google Cloud, BigQuery, server infrastructure, and automated jobs
• Internal applications, back-office automation, and operational tools
• Websites, focused repairs, and small builds from design through launch

The result: a working technical system, tested against real use and documented for the people who maintain it.

Which channels deserve the next dollar? I connect media activity to customer response, examine how credit is assigned, and make the limits of the measurement clear enough to act on.

• Attribution audits and model design
• TV and radio response measurement through Quality Analytics
• Channel performance connected to acquisition cost and customer value
• Reporting that makes media decisions and assumptions inspectable

The result: a defensible way to compare performance, with the assumptions and limitations visible.

Missing events, duplicate conversions, and inconsistent definitions make every downstream answer harder. I audit and implement the collection layer, from a single site to a portfolio of brands.

• GA4 and Google Tag Manager audits and implementations
• Server-side tagging, data layers, and event design
• Enterprise migrations and multi-brand measurement standards
• Validation, documentation, and reporting checks

The result: a documented measurement foundation with events that mean the same thing across properties.

Some problems call for one focused build: understand the need, build the thing, and leave it in working order.

• A website, internal tool, report, or automation with a clear finish line
• One API connection or a repetitive workflow automated
• A focused analytics audit or implementation repair
• A small data model, dashboard, or integration delivered with documentation

The result: a working deliverable, tested against real use and documented for the people who maintain it.