A
Not Specified Permanent

Seattle, Washington · USA job

Applied Scientist II, Amazon Fulfillment Technology , Amazon Fulfillment Technologies (AFT)

Amazon

Seattle, Washington

Job description

Overview

As an Applied Scientist at AFT Science, you will design and automate optimization, simulation, and ML solutions for Amazon's Fulfillment Network. You'll work with cross-functional teams to improve process efficiency and associate experience at scale. You will build scalable models and prototypes, validate them with experiments, and help deploy production-ready solutions. This role offers the opportunity to tackle high-impact, real-world problems in a globally distributed fulfillment system.

Compensation / Benefits
  • Medical, Dental, and Vision
  • Maternity and Parental Leave Options
  • Paid Time Off (PTO)
  • 401(k) Plan
  • RSUs
  • Competitive health benefits
Responsibilities
  • Develop domain understanding of operational processes, system architecture, and business needs
  • Deep dive data and code to identify improvement opportunities or disruptive approaches
  • Create scalable mathematical models for production systems to derive optimal or near-optimal solutions
  • Build prototypes and simulations for agile experimentation of devised solutions
  • Advocate technical solutions to stakeholders and leadership
  • Collaborate with engineers to integrate prototypes into production systems
  • Design experiments and metrics to test new or incremental production solutions
  • Partner with teams to drive impact on efficiency and associate experience
Key requirements
  • PhD, or Master's degree and 4+ years of science, technology, engineering or related field experience
  • 2+ years of building models for business applications
  • Experience programming in Java, C++, Python or related language
  • Applied research experience in operations research, optimization, machine learning, statistics or related field
  • Effective communication with stakeholders
  • Strong collaboration across cross-functional teams
  • Analytical mindset with problem-solving drive
  • Operations research
  • Optimization
  • Machine learning

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