The Amazon Fulfillment Technologies (AFT) Science team is looking for an exceptional Applied Scientist, with strong optimization and analytical skills, to develop production solutions for one of the most complex systems in the world: Amazon’s Fulfillment Network. At AFT Science, we design, build and deploy optimization, simulation, and machine learning solutions to power the production systems running at world wide Amazon Fulfillment Centers. We solve a wide range of problems that are encountered in the network, including labor planning and staffing, demand prioritization, pick assignment and scheduling, and flow process optimization. We are tasked to develop innovative, scalable, and reliable science-driven solutions that are beyond the published state of art in order to run frequently (ranging from every few minutes to every few hours per use case) and continuously in our large scale network.

* Develop an understanding and domain knowledge of operational processes, system architecture and functions, and business requirements

* Deep dive into data and code to identify opportunities for continuous improvement and/or disruptive new approach

* Develop scalable mathematical models for production systems to derive optimal or near-optimal solutions for existing and new challenges

* Create prototypes and simulations for agile experimentation of devised solutions

* Advocate technical solutions to business stakeholders, engineering teams, and senior leadership

* Partner with engineers to integrate prototypes into production systems

* Design experiment to test new or incremental solutions launched in production and build metrics to track performance