Data Scientist Demand Forecasting (Bengaluru)

Job Description Summary We are hiring an experienced Data Scientist to design and deploy demand forecasting and pricing simulation models for Retail/CPG use cases. This role owns the complete ML lifecycle from data exploration to production deployment on AWS SageMaker and works closely with business stakeholders to convert model output into decisions that directly impact revenue and margin. Key Responsibilities - Design, build, and deploy scalable demand forecasting models (time-series and ML-based) to predict product demand at SKU, category, channel, and regional levels - Build what-if simulation tools for discount and pricing strategies to optimize margin - Own the end-to-end ML lifecycle: data exploration, feature engineering, model training, validation, deployment, monitoring, and iteration - Build, train, and deploy models on AWS SageMaker; manage pipelines, endpoints, and model versioning in a cloud-native environment - Translate complex analytical output into clear, actionable recommendations for business and senior leadership - Build automated Power BI reports to track demand forecast performance - Partner with Data Engineering teams to build robust, scalable pipelines supporting model training and inference Required Skills Mandatory - 68 years hands-on experience in Data Science, Machine Learning, or Advanced Analytics - Robust experience in demand forecasting (ARIMA, Prophet, LSTM, XGBoost, or similar) - Proven expertise in pricing/discount simulation price elasticity modeling, scenario analysis - Deep understanding of at least two Retail/CPG use cases: customer segmentation, recommendations, demand forecasting, sentiment analysis, inventory optimization, promotion uplift modeling, campaign analysis, or churn prediction - Hands-on production experience with AWS SageMaker model training, hyperparameter tuning, deployment, batch and real-time inference - Advanced Python (pandas, NumPy, scikit-learn, TensorFlow/PyTorch) and SQL for data extracti .