Applied Scientist, Worldwide Grocery Stores - Data and Science
Core
Build demand and labor forecasting models to drive staffing efficiency and capacity decisions across the Amazon Grocery Network.
Role type
Applied Scientist (Forecasting & Supply Chain Science)
Builds
Production ML models for demand and labor forecasting
Domain
Retail / Grocery / Supply Chain
Deliverable
production ML models
Required skills
Time-series modeling, Bayesian methods, Machine Learning, Python (scientific computing/ML libraries), SQL, Large-scale data processing
Preferred skills
Generative AI for forecasting, Cloud model deployment (SageMaker/EC2), Peer-reviewed publications
Technologies
pandas, NumPy, scikit-learn, Redshift, Spark, EMR, SageMaker, EC2, AWS Batch
Responsibilities
Develop and deploy demand/labor forecasting models; Translate business problems into scientific solutions; Analyze forecast performance and downstream impact; Prototype Generative AI approaches; Partner with engineering to build scalable systems; Monitor deployed models and improve quality; Communicate technical concepts to stakeholders.
Seniority
Mid-Senior, hands-on IC