Requirements

• Proficiency in Python and PySpark for data analysis, machine learning, and demand forecasting (regression + time series models)
• Experience with forecasting models such as LightGBM/ XGBoost and classical time series methods (e.g., ETS/ARIMA)
• Strong understanding of the machine learning workflow (data cleansing, feature engineering, model evaluation, model explainability)
• Familiarity with forecasting evaluation metrics (e.g. MAPE, MAE) and ability to validate model performance
• Strong SQL skills for managing and querying large datasets
• Knowledge of data visualization tools (e.g., Power BI)
• Experience with cloud-based technologies such as Databricks, Azure, or AWS
• Strong communication skills — able to explain insights and models to both business and techni...