We implemented a comprehensive demand forecasting solution. This involved: designing and building robust data engineering pipelines for preprocessing vast datasets from various sources (sales history, promotions, external factors); developing and deploying multiple Machine Learning models (e.g., time series, ensemble methods) that were evaluated and fine-tuned to predict the optimal demand for various products.