VP of Data.
ML Patent Holder. Recovering Medievalist.
I build data functions from scratch and ship ML systems that stay in production. I’ve done this at companies ranging from enterprise to pre-Series A, most recently as VP of Data at Cookie Finance.
Along the way I’ve patented two production ML systems for market sizing and growth forecasting, published on AI strategy, and broken out my ELI5 explanation of LLMs for a variety of stakeholders.
My background is unusual: I came to statistics through linguistics, which means I think carefully about what language does and doesn’t communicate, including what data does and doesn’t tell you.
Patents
Total Addressable Market Analysis System
Brussow, J., Danial, P., Waterman, C. (2024). Machine learning system and method for total addressable market assessments in connection with keyword qualification (U.S. Patent No. 12,182,217).
Online Performance Marketing Growth Projections
Brussow, J., Danial, P., Pasquarella, C. (2025). Machine learning system and method for targeted growth projection of market inquiry results (U.S. Patent No. 12,353,492).
Work Experience
I’m currently VP of Data at Cookie Finance, where I’m building data and AI products to support creators.
With over 13 years of experience in the data field, my full work history deserves its own page. You can see my career journey by clicking through.
Publications on AI Strategy
My recent published writing has focused primarily on AI strategy for marketing and brand audiences. I’m increasingly writing about data infrastructure, organizational AI adoption, and what it actually takes to build ML systems that survive contact with reality.
Technical Stack
Unlike many data executives, I still write and ship production code.
Current stack: Python, SQL, AWS (Lambda, SageMaker, API Gateway, S3), Snowflake, dbt, Prefect, Tableau, Git.
I build with LLMs across providers: Codex, Claude, and open-source variants including LLaMA and Mistral.
Education
Ph.D., Research, Evaluation, Measurement, and Statistics, University of Kansas
Graduated with honors.
Dissertation: Finding Item-Level Causes of Differential Item Functioning: A Hierarchical IRT Model for Explaining DIF
MA, English Language Studies, University of Kansas
Thesis: Wundorlice hit hæleþ: Organization and Metatextual Markers in Old English Recipes
BAs, English & Germanic Languages and Literature, University of Kansas
Graduated summa cum laude with Honors Program completion and Departmental Honors in English.