Experience with methods such as gradient boosting, regression, tree-based models, classical statistical forecasting, probabilistic forecasting, or deep-learning approaches to temporal data is relevant. We are specifically looking for experience building predictive models where time, historical patterns, seasonality, trends, and future outcomes matter .