Data Scientist

Data Scientist (6-15 yrs)

Key Responsibilities :

- Demand Forecasting : Design, build, and deploy scalable demand forecasting models (time-series, ML-based) to predict product demand at SKU, category, channel, and regional levels.

- Discount & Price Simulation : Build what-if simulation tools to optimize discount strategies and maximize margin.

- End-to-End Model Ownership : Own the full ML lifecycle - data exploration, feature engineering, model training, validation, deployment, monitoring, and iteration.

- Production Deployment on AWS : Build, train, and deploy models using AWS SageMaker; manage pipelines, endpoints, and model versioning in cloud-native environments.

- Stakeholder Collaboration : Translate complex analytical outputs into clear, actionable insights for business leaders; present findings and recommendations to senior leadership.

- Power BI : Create automated reports to present and track demand forecast model output.

- Data Pipeline Development : Collaborate with Data Engineers to build robust, scalable data pipelines supporting model training and inference.

Must-Have Skills :

- 6 - 8 years of hands-on experience in Data Science, Machine Learning, or Advanced Analytics.

- Strong experience in Demand Forecasting (ARIMA, Prophet, LSTM, XGBoost, or similar).

- Proven expertise in Pricing/Discount Simulation (price elasticity modeling, scenario analysis).

- Must have deep understanding of at least couple of Retail/CPG use cases such as customer segmentation, recommendations, demand forecasting, sentiment analysis, inventory optimization, promotion uplift modeling, campaign analysis, churn prediction etc.

- Hands-on production experience with AWS SageMaker (model training, hyperparameter tuning, deployment, batch/real-time inference).

- Programming : Advanced Python (pandas, NumPy, scikit-learn, TensorFlow/PyTorch); SQL for data extraction and transformation.

- Statistical & ML Techniques : Regression, classification, time-series forecasting, ensemble methods, feature engineering.

- Stakeholder Management : Ability to communicate technical concepts to non-technical audiences and influence business decisions.

- Education : Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Engineering, Economics, or related quantitative field.