AI Product Management
Senior AI PM / I build AI products end-to-end / I code the models I ship
My background in chemical engineering trained me to analyze how complex systems fail, not just optimize what is already there. For the past seven years, I have applied that instinct to artificial intelligence—owning a portfolio of 18 AI/ML products utilized by over 4,000 users across enterprise risk frameworks and compliance operations.
Most AI failures are not model failures. They are adoption bottlenecks, incentive misalignments, or trust gaps. These are strategy problems before they are engineering problems.
I bridge that gap by setting portfolio-level investment strategies, managing governance frameworks, and maintaining the technical capability to code and validate the models I ship. I focus on owning both strategy and delivery to drive deterministic, high-value organizational outcomes.
Core Applications & Projects
Writing & Insights
- 2026-04-17 Why Leadership Builds AI Tools Nobody Uses
- 2026-04-12 If You Can't Measure It, You Can't Govern It
- 2026-03-31 How Chemical Engineering Shaped How I Think as a Product Manager
- 2026-03-10 If You Build It, Will They Come? - Why Your AI Model's Explainability Might Be the Problem
- 2026-01-25 Stick a Fork In it
- 2022-10-05 USA Real Estate - Predicting Sales Price
- 2022-09-18 Predicting Attrition in Healthcare Industry
- 2022-09-12 AirBnB Open Data EDA
- 2017-01-06 Why Do Good Employees Leave?
- 2016-12-11 Short-Term Rental Platform vs Long-Term Tenant: Evaluating Expected Profits
- 2016-11-08 KMeans++ Cluster Analysis using PCA on Airport Delays
- 2016-11-01 Classification Model of Predicting Movie Ratings Prior to Being Released
- 2016-10-25 A Classification Analysis of Titanic Survivors
- 2016-10-19 Predicting Data Scientist Salaries Using Logistic Regression
- 2016-10-12 Iowa Liquor Market Research: Evaluation of New Market Entry
- 2016-10-04 Evaluating Year 2000 Billboard Top 100 Data Set