This document discusses using SciPy and real-time big data for site optimization. It describes a system using Kafka, Storm, SciPy and a Bayesian bandit algorithm to test different variations of content like headlines on a website to maximize click-through rates. The system analyzes impressions and click data in real-time to decide which variation to show users and improves its confidence in the estimated click-through rates of each variation as it receives more data.