Forecasting Scientist, Labor & AI

Amazon; Seattle (WA); On-site; USD 136,000 - 184,000; Full time

Job summary

Amazon’s Worldwide Grocery Stores (WWGS) Data & Science team is seeking an Applied Scientist to join our S&OP and Supply Chain Science efforts in Seattle. You will help build forecasting models that drive labor planning across the Amazon Grocery Network and collaborate with engineers, product managers, and business stakeholders.

You will develop and deploy time-series, Bayesian, and ML models, explore Generative AI enhancements, and translate complex problems into actionable scientific solutions

Qualifications

• Master’s degree or above in Engineering, Computer Science, Machine Learning, Statistics, Physics, or related fields.
• Experience building machine learning models or developing algorithms for business application.
• Proficiency in Python, including scientific computing and ML libraries (e.g., pandas, NumPy, scikit-learn)
• Experience with SQL and large-scale data processing on a modern data platform (e.g., Redshift, Spark, EMR, or equivalent data warehouse)

Responsibilities

• Develop, evaluate, and deploy components of our demand and labor forecasting models, including statistical time-series, Bayesian, and machine-learning models with distributional objectives, with input and guidance from senior scientists.
• Translate business problems into well-defined scientific solutions with clear objectives, constraints, and success metrics, partnering with senior scientists on the more ambiguous ones.
• Analyze forecast performance and downstream impact on labor planning and capacity decisions; develop metrics that reflect business outcomes, not only forecast accuracy.
• Prototype and evaluate Generative AI approaches in our forecasting workflows and help productionize the ones that succeed.
• Partner with engineering teams to produce models, contribute to data pipelines, and build scalable, maintainable forecasting systems.
• Monitor deployed models, investigate performance issues, and continuously improve model quality and calibration.
• Communicate technical concepts and recommendations clearly through documentation, presentations, and design reviews with scientists, engineers, product managers, and business leaders.
• Contribute to the internal scientific community through knowledge sharing and, where appropriate, research publications.

Skills

ML model development

Python

SQL

Education

Master’s degree or above in Engineering, Computer Science, Machine Learning, Statistics, Physics, or related fields

Tools

scikit-learn

Pandas

NumPy

Redshift

Spark

EMR

Job description

Amazon’s Worldwide Grocery Stores (WWGS) Data & Science team is seeking an Applied Scientist to join our S&OP and Supply Chain Science efforts in Seattle. You will help build forecasting models that drive labor planning across the Amazon Grocery Network and collaborate with engineers, product managers, and business stakeholders.

You will develop and deploy time-series, Bayesian, and ML models, explore Generative AI enhancements, and translate complex problems into actionable scientific solutions