Accessibility Technology
Systems Engineering
Data Mining
Forecasting
Enabled Autonomy
Accessibility Technology for Watching Videos
Featuring:
Automated Browsing Experience
Simple Touch for Selection
Responsive Visual & Audio Feedback
Auto Screen Off if Unused
Disabled System Menu and Display
Cloud Synced Videos (No Download Delays)
Hi, welcome.This website provides weekly reporting for the Enabled Autonomy Video Player tablet and other data signals. The main goal is to support evidence-based improvements for the app and other projects by monitoring and forecasting key measurements.I created the Enabled Autonomy Video Player app for my cousin, Bill (cognitively impaired), to provide him a video browsing and viewing experience he can engage with independently.
365 Retail Markets
Senior Data Analyst
2025 - present
Created (0-to-1) a recommendation system for routing, restocking and merchandising. Weekly runs from an automated backend (dbt / Snowflake / Airflow) reach a client-facing frontend with evidence for each action and an AI chat feature; validated against operator behavior by backtesting.
Sole developer of a personalized product recommendation data product, served within a consumer-facing app (impact: +8.3% spending per customer).
Estimated theft from cancel rate for ~45k U.S. unattended retail locations; delivered a client-ready dashboard with ROI estimates, adopted by the sales team.
Little Caesars
Data Scientist
2021 - 2024
Standardized data pipelines for order, customer, and store-level measurement, supporting business-wide analytics (marketing promotions, test items, operational changes).
Created foundational customer segmentation methodology based on retention/churn modeling, used by the marketing partnership for targeted and programmatic marketing.
Led development for item-specific demand predictions served daily to store operators at each domestic and international location.
Casper Sleep
Data Scientist
2019
Media-mix modeling: designed a data pipeline and Bayesian regression model optimizing channel-by-funnel ad spending, highlighting diminishing returns and underused channels.
Developed a dashboard visualizing ad-spend response curves for channel-by-funnel targets.
Reviewed and adjusted existing advertising testing methods, including geospatial A/B testing.
University of Lausanne
Data Scientist and Course Instructor
2014 - 2018
Developed a sequential Monte Carlo model with parameter estimation via a generalized linear mixed model, testing competing theories of memory-based decision making.
Designed the computer-based experiments behind it and evaluated predictive accuracy against the behavioral results they produced.
Secured 2-year postdoctoral salary funding from the Swiss National Science Foundation (260K CHF).
Education
Ph.D. in Cognitive and Brain Sciences
State University of New York at Binghamton
B.S. (Summa cum laude) in Psychology
Eastern Michigan University