Applied ML & Data Science
I build ML systems that ship to production and move business metrics. Currently leading Data Science & Data Engineering at Fashionphile.
About Me
I build machine learning systems that ship to production and move business metrics. Currently leading Data Science and Data Engineering at Fashionphile, where my team owns pricing algorithms, inventory forecasting, and the data infrastructure powering one of the largest luxury resale platforms in the US. Previously drove $30M+ in revenue at Newegg through recommendation engines and deployed NLP pipelines on 40K+ documents at Mortenson.
Learn more about my journey →Featured Work
Recommendation Engine — $30M Revenue Impact
Built a product recommendation engine at Newegg that lifted Average Order Value by 18% and added $30M in annual revenue. Led customer segmentation with Spark ML and 100+ A/B tests.
Real-Time Fraud Detection — $12M Saved
Developed real-time fraud detection using ensemble methods, cutting fraud by 60% and saving $12M yearly at a NASDAQ-listed e-commerce company.
BERT NLP Pipeline — 40K+ Documents
Deployed BERT-based NLP pipelines for internal project document classification at a top-10 US construction firm. Reduced project scoping from 2 weeks to 2 days.
Publications
American Sign Language Recognition using Deep Learning
Research on applying deep learning techniques (CNN, VGG16, Inception Net, RESNET) for recognizing American Sign Language gestures, improving communication accessibility.
Read the paper →