Job Summary
We are seeking a Data Scientist with expertise in data science and operations research to develop predictive models and optimization solutions. The role focuses on time-series forecasting, machine learning, demand planning, and inventory optimization across products, regions, business segments, retail stores, distribution centers, hubs, and customer-facing nodes. The Data Scientist will develop SQL-based ETL processes and data pipelines, evaluate model performance, collaborate with data engineering and cross-functional teams to productionize and scale solutions, and establish governance and monitoring practices to ensure models are accurate, explainable, auditable, and production-ready.
Key Responsibilities
• Develop and deploy time-series forecasting and machine learning models to improve demand planning across products, regions, and business segments.
• Apply operations research and optimization techniques to improve outcomes using available resources and operational capabilities.
• Develop and maintain SQL-based ETL processes and data pipelines supporting optimization models, scenario analysis, and production deployment.
• Partner with data engineering teams to ensure the quality, availability, and integrity of model inputs.
• Incorporate demand variability, lead times, network structure, service policies, and operational constraints into model inputs and optimization solutions.
• Evaluate model performance using accuracy, bias, SMAPE, forecast attainment, and other relevant metrics.
• Collaborate with cross-functional teams to productionize and scale data science solutions.
• Lead the end-to-end development and ownership of Multi-Echelon Inventory Optimization (MEIO) models across retail stores, distribution centers, hubs, and customer-facing nodes.
• Establish governance, monitoring, and documentation practices to ensure model outputs are accurate, explainable, auditable, and production-ready.
Required Qualifications
• Experience in data science, predictive modeling, and machine learning.
• Experience with time-series forecasting and demand planning.
• Knowledge of operations research and optimization techniques.
• Experience developing and maintaining SQL-based ETL processes and data pipelines.
• Experience evaluating model performance using metrics such as accuracy, bias, SMAPE, and forecast attainment.
• Ability to collaborate with data engineering and cross-functional teams to maintain data quality, availability, and integrity and support production deployment.
• Understanding of model governance, monitoring, explainability, auditability, and production deployment.
• Experience developing and managing inventory optimization models, preferably Multi-Echelon Inventory Optimization (MEIO).
