Python + Time Series Forecasting

Job Summary

JD- Having a background in Retail will be a Big Plus. Advanced in Python: Proven experience with core libraries like pandas, numpy, scikit-learn, and matplotlib, plus advanced tools like statsmodels, xgboost, lightgbm, prophet, deep learning-based forecasting (e.g. Neural forecast). Advanced Forecasting Techniques: Experience with ensemble models, hierarchical forecasting, probabilistic forecasting, and multivariate time series. Pricing Models: Background in price elasticity modeling, good to have experience in optimization - at least one of the 2 resources Model Evaluation: Familiarity with time-series cross-validation, backtesting, and metrics such as MAE, MAPE, RMSE, SMAPE, and prediction intervals. SQL Proficiency: Ability to query and manage data from relational databases. Version Control: Comfortable working with Git/GitHub for collaboration and code management. Mandate skill- python and advanced forcesting skills with models like arima etc. Any shift- Second shift Location-Banglore