Applied Scientist, Worldwide Grocery Stores, Data and Science
Core
Build machine learning and statistical models to optimize grocery supply chain planning, inventory stocking, and product availability, reducing out-of-stocks and waste.
Role type
Applied Scientist (Supply Chain Science & ML)
Builds
Demand forecasting models, customer preference models, and Generative AI tools for supply chain workflows.
Domain
Grocery retail, Supply Chain, Machine Learning
Deliverable
production ML models
Required skills
Machine learning model development, Time series analysis, Bayesian methods, Python (scientific computing/ML libraries), SQL, Large-scale data processing
Preferred skills
Supply chain modeling, Cloud development (AWS), Large language models, Agentic frameworks, Research publications
Technologies
Python, pandas, NumPy, scikit-learn, Redshift, Spark, EMR, AWS, Generative AI
Responsibilities
Develop and deploy ML/statistical models for demand forecasting and product availability; Build mechanisms to reduce out-of-stocks and shrink; Translate business problems into scientific solutions with clear metrics; Analyze model performance and downstream impact on inventory decisions; Prototype and productionize Generative AI approaches for automated interventions; Partner with engineering to build scalable science systems; Monitor deployed models and improve calibration; Communicate technical concepts to stakeholders.
Seniority
Mid-level IC (Master's required, guidance from senior scientists)