This repo contains a GBQ script that pulls, cleans, and aggregates data of a hybrid experiment (AB & diff-in-diff). The R script contains a logic that analyzes the performance and significance of the results according to key success metrics

End-to-end data science project to analyze Uber ride pricing and predict fares and surge multipliers, with ML models and a Streamlit app for interactive fare estimation.

AI-powered Surge Pricing & ETA Optimization for ride-hailing platforms. Using demand forecasting and real-time ETA predictions, it optimizes fares, reduces wait times, and improves driver/passenger experience. Optimized for Tehran, it helps increase revenue and reduce pricing volatility.