Applied Scientist

Job description

DESCRIPTION

Amazon is looking for a motivated individual with strong analytical skills and practical experience to join our Modeling and Optimization (MOP) team. We are hiring specialists at all levels into our scientific team with expertise in network and combinatorial optimization, algorithms, data structures, statistics, and/or machine learning.

Amazon.com is a multi-billion dollar company that is growing rapidly. Because we are driven by faster delivery to customers, a more efficient supply chain network, and lower cost of operations, our main focus is to utilize available data in the development of analytical modeling and visualization tools. As part of the MOP Routing Science team, your main focus will be on developing and improving to our last-mile experience, with emphasis on algorithmic and analytical work.

You will also play an integral role in the network planning, modeling, and analysis that will improve the efficiency and cost effectiveness of global fulfillment operations. You will identify and evaluate opportunities to reduce variable costs by improving the transportation network topology, inventory placement, transportation operations and scheduling, fulfillment center processes, and the execution to operational plans. You will also improve the efficiency of capital investment by helping plan the location and deployment of fixed assets. Finally, you will help create the metrics to quantify improvements to the fulfillment costs (e.g., transportation and labor costs) resulting from the application of these optimization models and tools.

Desired profile

BASIC QUALIFICATIONS

· Master's degree in Computer Science, Operations Research, Statistics, Applied Mathematics, or a related field and at least 3 years work experience, or a PhD with demonstrated practical experience through industrial internships
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· Experience in designing analytic and/or algorithmic solutions to business or operational problems
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· Experience implementing algorithms, tailored to particular business needs and tested on large data sets
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· Experience writing scripts (e.g.: Python, Ruby, Perl, etc...) to manipulate data and developing software in traditional programming languages (C++, Java, etc..).
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· Excellent communication skills with both technical and non-technical audiences.