Your question is Time Series Forecasting Methods. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
Can you describe your experience with time series forecasting and which methods you prefer?
Discuss how you select among approaches such as seasonal naive baselines, exponential smoothing, ARIMA or SARIMA, and tree-based machine learning models. Explain your feature engineering, time-aware validation, evaluation metrics, handling of seasonality and missing observations, and how you would deploy and monitor a forecasting model. Include a concise practical implementation or pseudocode example showing your preferred workflow.