• Own the lifecycle of forecasting models across various departments (e.g., Finance, Operations, Marketing). • Develop, back-test, validate, and deploy predictive models using statistical techniques such as time series analysis, regression, ARIMA, exponential smoothing, and related methods. • Define and monitor model performance metrics (e.g., MAPE, RMSE, bias); perform ongoing forecast-vs-actual analysis to identify drivers of variance and continuously improve accuracy. • Design scenario-based forecasts (best case, worst case, most likely) to support planning under uncertainty. • Write complex, highly optimized SQL queries (CTEs, window functions, advanced joins) to extract, transform, and aggregate data from the data warehouse. • Partner closely with Data Engineering to define data requirements, improve data quality, and ensure consistency of metrics used in forecasting. • Build and automate reliable data pipelines so forecasts are refreshed on a consistent and scalable cadence. • Design, build, and maintain executive-level dashboards in Looker to surface forecasts, trends, and key drivers. • Partner with functional leaders to understand business drivers, operational constraints, seasonality, and external market dynamics.