Applied Scientist: Global Grocery Forecasting & AI

Socket.dev; Seattle, Northern (WA, KY); Hybrid; USD 136,000 - 184,000; Full time

Job summary

Amazon’s Worldwide Grocery Stores (WWGS), Data & Science team seeks an Applied Scientist to join the S&OP and Supply Chain Science group in Seattle. You will help build forecasting models that drive labor planning across the Grocery Network, affecting staffing efficiency and costs.

You’ll develop demand and labor forecasting models using Time-series, Bayesian, and ML methods, collaborating with senior scientists, engineers, PMs and business leaders to influence decisions and roadmap.

Qualifications

• Master's degree or above in Engineering, CS, ML, Statistics, Physics, or related fields.
• Experience building ML models or algorithms for business applications.
• Proficiency in Python with ML libraries (pandas, NumPy, scikit-learn).
• Experience with SQL and large-scale data processing on a modern data platform (Redshift, Spark, EMR).

Responsibilities

• Develop, evaluate, and deploy components of demand and labor forecasting models, including time-series, Bayesian, and ML models.
• Translate business problems into well-defined scientific solutions with clear objectives and success metrics.
• Analyze forecast performance and downstream impact on labor planning and capacity decisions.
• Prototype and evaluate Generative AI approaches in forecasting workflows and productionize successful ones.
• Partner with engineering teams to produce models, data pipelines, and scalable forecasting systems.
• Monitor deployed models and continuously improve model quality and calibration.
• Communicate technical concepts and recommendations through docs, presentations, and design reviews.
• Contribute to the internal scientific community through knowledge sharing and publications.

Skills

Machine learning modeling

Python (ML libs)

SQL & data processing

Education

Master's degree or above in STEM

Tools

Redshift

Spark

EMR

Job description

Amazon’s Worldwide Grocery Stores (WWGS), Data & Science team seeks an Applied Scientist to join the S&OP and Supply Chain Science group in Seattle. You will help build forecasting models that drive labor planning across the Grocery Network, affecting staffing efficiency and costs.

You’ll develop demand and labor forecasting models using Time-series, Bayesian, and ML methods, collaborating with senior scientists, engineers, PMs and business leaders to influence decisions and roadmap.