Head of Machine Learning & Data Science at Fetch Loyalty App (2018-06 – 2023-09)
$1B in Rewards Earned
- Founded and scaled ML/data science team from 4 to 30, hiring data engineers, ML engineers, analysts, and data scientists
- Developed zero-defect PySpark consumer targeting system used by 100% of clients over 5 years, enabling revenue growth to $90M
- Trained BERT LLM to identify 37M incremental consumer products, monetized in client insights and automated using Sagemaker Estimator
- Built graph neural network anomaly detection system using PyTorch Geometric for coupon redemptions with Streamlit dashboard
- Developed promotion personalization model using logistic regression achieving 81.5% recall
- Built recommender system correctly identifying 3 of 5 subsequent category purchases
- Delivered statistical outlier detection for pricing data via Airflow and DBT, eliminating client reporting errors
- Introduced test/control ROI measurement methodology, cementing company reputation for scientific marketing
Director of Data Analytics at Catalina (2014-04 – 2016-11)
World's Largest Shopper Database
- Delivered major statistical experiment establishing 3x return on manufacturer promotions, increasing client contract negotiation leverage
- Developed ensemble model to predict promotional responsiveness of Beauty category shoppers
- Measured test vs. control promotion performance for over $5M in marketing investments
- Oversaw A/B testing for Big Data/Personalization product launch
- Delivered customer segmentation quantifying opportunity across engagement levels
Analytics Manager, Digital & Healthcare at Walgreen Co. (2007-01 – 2014-03)
- Founded analytics function serving digital pharmacy and telehealth business lines, building and leading team of 7
- Quantified HIV business performance, influencing management to execute major acquisition closing $300M revenue gap
- Led LTV measurement of online vs. mobile app users, driving investment in email capture strategy
- Performed customer journey analysis generating product ideas (proactive chat, online appointment scheduling)
Data Analyst at Leo Burnett (2004-02 – 2006-12)
- Quantified need to reduce investment in underperforming program, saving $13M
- Deployed segmentation for audience selection resulting in 17% higher response rates
- Corrected event booking policy increasing capacity utilization from 85% to 97%
