Electricity Maps maintains a comprehensive hourly dataset for electricity generation and exchanges. Our most recent work leveraged this dataset to predict the best hour to use electricity to minimize carbon footprint. We will present how we broke down electricity generation into granular time series production events which can be forecasted with simple Lasso models and the infrastructure we built to support it. We will discuss challenges we encountered along the way and how we used those predictions to deploy a carbon aware scheduler for running our computational workloads. Finally, we will present our evaluation of avoided emissions using this scheduler.