Amazon's Modeling and Optimization team (MOP) is looking for a Research Scientist to optimize one of the most complex logistics systems in the world.
Academic and / or practical background in Computer Science, Engineering, Operations Research, or Process Control are particularly relevant for this position.
Experience in the integration of model-based engineering tools and / or multidisciplinary analysis & optimization is also a plus.
Amazon’s extensive logistics system comprises thousands of fixed infrastructure nodes with millions of possible connections between them.
Billions of packages flow through this network on a yearly basis, making the impact of optimal improvements truly unparalleled.
This magnificent challenge is a terrific opportunity to understand, model, simulate, optimize, and reshape one of the world's most complex systems.
Your main focus will be improving the computational efficiency of model-based optimization tools, at various levels of fidelity, used in designing our transportation network.
You will make the real complexity of our logistics system visible, tangible, and manageable using cutting edge algorithmic methods.
You will integrate modeling and simulation capabilities to validate assumptions on the intricate interactions among different elements of our system.
You will identify and evaluate opportunities to improve customer experience, network speed, cost, and the efficiency of capital investment.
You will improve the capability of systems analyses that use optimization, simulation, and machine learning techniques. You will quantify the improvements resulting from the application of these tools and you will evaluate trade-
offs between competing outputs of the system.
This position requires drive and self-motivation, superior analytical thinking, data-driven disposition, application of technical knowledge to a business context, effective collaboration with fellow research scientists, software development engineers, and product managers, effective communication of technical designs to technical and non-
technical audiences, and 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
PhD degree in Computer Science, Applied Mathematics, Operations Research or a related field, or a Master's degree and at least 5 years of relevant work experience
Experience in designing analytic and / or algorithmic solutions to business or operational problems
Experience implementing algorithms, tailored to particular business needs and tested on large data sets
Exposure to scripting languages (Python, Ruby, etc.), SQL and Statistical tools, major object-oriented programming languages (java, C++, etc.
optimization software and libraries (XPRESS, CPLEX, 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.
Amazon is an Equal Opportunity Employer Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.
PhD in Computer Science, Operations Research, or related Engineering or Applied Sciences fields
Previous work experience or demonstrated practical experience through industrial internships
A proven record of innovation and driving critical research in Applied Optimization in industry, government, or military
Experience developing intricate systems, including establishing target system results and operation tolerances, developing a system design, analyzing this design use in relation to the function of the elements in the system, developing system prototypes, and testing and validating the developed design to quantify its value
Excellent interpersonal skills and a can-do never-give-up attitude
Experience with scripting languages (Python, Ruby, etc.), SQL, object-oriented programming languages (java, C++, etc.), optimization software and libraries (XPRESS, CPLEX, Gurobi, SAS, R, etc.), and simulation software
Exposure to relational databases and Linux