Role Summary:

We are seeking a Lead/Architect Data Scientist to join our team in Bengaluru. This role will focus on building and deploying advanced forecasting models and pricing/discount simulation engines to optimize inventory, revenue, and profitability across retail operations. Work closely with cross-functional teams including Merchandising, Planning, Pricing, and Supply Chain to deliver production-grade ML solutions that drive strategic business decisions.

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: 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:





- 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

Good-to-Have Skills:

- Experience in retail, fashion, footwear, or consumer goods industries
- Familiarity with MLOps best practices (CI/CD for ML, model monitoring, drift detection)
- Experience with Azure ecosystem (Azure ML) or other cloud platforms
- Knowledge of Airflow, Snowflake, dbt or similar up-to-date data stack tools

📌 Lead/Architect - Data Scientist (Bengaluru)
🏢 QBurst
📍 Bengaluru