Operations Research Scientist

Job description

DESCRIPTION

Amazon's Customer Service Worldwide Capacity Planning team (CSWWCP) is looking for a motivated individual with strong analytical skills and practical experience to optimize one of the most complex service network systems in the world. We are hiring specialists at all levels with expertise in Queuing Theory, Simulation, Optimization, Algorithm Design, and/or Machine Learning.

Amazon.com strives to be Earth's most customer-centric company, and CS-WWCP is responsible for planning for the Global Customer Service network that ensures we are available when our customers need us. Our Operations Research team is tasked with designing algorithms and systems for all stages of the planning process, from long-term headcount planning optimization, to short-term scheduling and real-time routing. We face challenges due to the enormous size and complexity of the network. It is composed of a large number of skills, languages and sites. Additionally, we must account for stochastic issues in all planning stages, as well as the difficulty of modeling human behavior, for both customers and agents.

The ideal candidate will have good communication skills and ability to speak at a level appropriate for the audience. They will collaborate effectively with fellow scientists, software development engineers, and product managers, and will deliver business value in close partnership with many stakeholders from Operations, Finance, IT, and Business Leadership.

Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation

Desired profile

BASIC QUALIFICATIONS

· PhD degree in Operations Research, Industrial Engineering, Transportation Engineering, Statistics, Applied Mathematics, Computer Science or related field, or a Master's degree and at least 5 years of relevant work experience
· Experience in designing, implementing, and testing analytic and/or algorithmic solutions to business or operational problems.
· Exposure to optimization software and libraries (XPRESS, Gurobi, CPLEX, etc.), scripting languages (Python, R, etc.), SQL and Statistical tools, major object-oriented programming languages (java, C++, etc.), and simulation software.
· Excellent communication skills with both technical and non-technical audiences
· Ability to work independently and as part of a diverse team.