The advertising industry runs on data most companies don't trust. I fix that — building the measurement infrastructure that makes ad spend accountable.
I specialize in the data engineering problems that keep adtech companies up at night: attribution pipelines that silently drop conversions, identity graphs with abysmal match rates, CTV measurement systems that can't reconcile across platforms. I've spent my career at the intersection of advertising and data infrastructure — building systems that process billions of events and turn them into numbers people can actually trust.
Before founding MindWyre, I built revenue-impacting pipelines at Disney (Hulu/Disney+ ad logs), optimized ad targeting at Pinterest, and developed proprietary attribution models tracking $3.5B in annual ad spend at Kochava. I know what breaks at scale, and I know how to fix it.
When I'm not debugging why your conversions vanished, you'll find me hiking Idaho's trails, spending time with my kids, or working toward my Master's in Analytics at Georgia Tech.
Martech Agency (Contract)
ETL pipelines for Experian and Liveramp ad-targeting. Media mix modeling, A/B test automation with VertexAI, and optimizing user match-rates for advertising partners.
Disney (Contract)
Built revenue-impacting data pipelines for Hulu, Disney+, and GAM ad-logs using GCP, Snowflake, Airflow, and Python. Engineered self-service reporting via Habu clean room integration.
Pinterest (Contract)
Automated insights generation for high-value advertisers using Presto, Spark SQL, and Pandas. Cohort analysis, campaign targeting optimization, and causal engagement analysis.
Kochava (Full-Time)
Proprietary attribution modeling on $3.5B in annual ad spend. Fraud detection algorithms, LTV calculation frameworks, and incremental lift studies for clients including TikTok.
Georgia Institute of Technology — In Progress
Lewis-Clark State College
Amazon Web Services Certification
Featured in App Developer Magazine
Let's figure out where your pipeline is leaking value — and fix it.