Applied Scientist, Large-Scale Optimization & Forecasting

Amazon; Bellevue (WA); On-site; USD 143,000 - 193,000; Full time

Benefits offered by this job

Health insurance

RSUs

Parental leave

401(k) matching

Job summary

Amazon's Supply Chain is the backbone of the fastest growing e-commerce business, and planning it is one of the largest optimization problems in industry. You will design and deploy large-scale optimization and forecasting models that plan inventory placement and flow across our EU/NA fulfillment network under uncertainty.

Join a team that decomposes complex network problems, builds production-grade cloud-native software, and partners with science, engineering, operations, and finance to take

Qualifications

• PhD or master's with CS/CE/ML-related experience.
• Proven publication or patent record preferred.
• Experience programming in Java, C++, Python or related language.

Responsibilities

• Build state-of-the-art, robust, and scalable stochastic optimization and probabilistic forecasting algorithms.
• Shape how large-scale planning problems are formulated, decomposed, and solved for computational performance.
• Engineer algorithms as production-grade, cloud-native software from prototype to deployment.
• Think several steps ahead and ship incremental improvements while driving long-term solutions.
• Prototype fast, drive pilots, and integrate operational feedback.

Skills

Large-scale optimization

Machine learning

Probabilistic forecasting

Decomposition methods

Production-grade software development

Communication to leadership

Education

PhD

Master's degree + CS/CE/ML

Tools

Java

C++

Python

Unix/Linux

Distributed computing frameworks

Job description

Amazon's Supply Chain is the backbone of the fastest growing e-commerce business, and planning it is one of the largest optimization problems in industry. You will design and deploy large-scale optimization and forecasting models that plan inventory placement and flow across our EU/NA fulfillment network under uncertainty.

Join a team that decomposes complex network problems, builds production-grade cloud-native software, and partners with science, engineering, operations, and finance to take