At PayPal, I lead Venmo’s P2P Ease of Payments Personalization Platform, building recommendation and ranking models that improve payment flows, friend discovery, transaction completion, and retention across millions of active users.
I also architected Venmo’s Experimentation Intelligence Framework, bringing automated A/B testing, power analysis, and causal measurement to hundreds of experiments. My work spans churn prediction, engagement forecasting, payment propensity scoring, instrumentation strategy, and scalable self-service analytics.
Previously at LinkedIn, I built fraud detection and connection-integrity pipelines for Recruiter, led causal research on InMail engagement, and designed experiments that informed product investment decisions. At McKinsey, I developed a Next Best Action engine that delivered over $10M in annual savings for a payments client.
I started at IBM, where I built tax-fraud models for the IRS that generated approximately $40M in annual savings. I enjoy translating complex modeling and experimentation insights into product strategy, customer growth, and measurable business outcomes.
