Applied Scientist — Global Logistics Optimization

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

Benefits offered by this job

Health insurance

RSUs

Sign-on bonus

401(k) matching

Paid time off

Job summary

Amazon Science's Modeling and Optimization (MOP) team seeks a candidate with strong analytical and algorithmic skills to optimize the global logistics network and its operations. You will enhance network efficiency through data-driven optimization and lead development of production-ready algorithms.

Responsibilities include guiding planning decisions, improving capacity and speed, and delivering measurable business impact.

Qualifications

• PhD required in Engineering, Computer Science, Machine Learning, Operations Research, Statistics, or related fields.
• Experience applying theoretical models in an applied environment.
• Experience programming in Java, C++, Python or related language.

Responsibilities

• Enhance global logistics network efficiency through data-driven optimization.
• Reduce variable costs by improving network design, inventory placement, process and operational planning, and resource allocation.
• Develop metrics to quantify business impact of implemented solutions.
• Lead development of production-ready algorithms and scientific tools for optimization and planning.

Skills

Java

C++

Python

Education

PhD in Engineering/CS/ML/OR/Statistics

Job description

Amazon Science's Modeling and Optimization (MOP) team seeks a candidate with strong analytical and algorithmic skills to optimize the global logistics network and its operations. You will enhance network efficiency through data-driven optimization and lead development of production-ready algorithms.

Responsibilities include guiding planning decisions, improving capacity and speed, and delivering measurable business impact.