Have you ever wondered how Amazon predicts when your order will arrive and how we ensure that it actually arrives on at the promised date/time? Have you wondered where all those Amazon semi-trucks on the road are headed? Are you passionate about increasing efficiency and reducing carbon footprint? Does the idea of having worldwide impact on Amazon's logistics network including our planes, trucks, and vans sound exciting to you? If so, then we want to talk with you! The Network Planning and Fulfillment Execution team owns and operates OR/ML and simulation systems that continually optimize the distribution of tens of millions of products across Amazon’s warehouses in the most cost-effective manner, utilizing large scale optimization techniques and distributed computing in trying to reduce overall transportation costs while improving the customer experience. We are focused on saving hundreds of millions of dollars using big data technologies, cutting edge science, machine learning, and scalable distributed software on the cloud that automates and optimizes inventory and shipments to customers under the uncertainty of demand, pricing and supply. We’re looking for a passionate, results-oriented, and inventive Research Scientist who can create and improve OR/ML models for our outbound transportation planning systems. In addition, you will be working on design, development and evaluation of highly innovative OR and ML models for solving complex business problems in the area of outbound transportation planning systems. More specifically, you will be developing a Mathematical Optimization model towards short term Origin-Destination flows that are inventory aware and adhere to facility capacities given destination demand. This will also require you to build machine learning models to predict inventory N weeks out (N<13 Weeks) and ML models to calibrate inventory bounds and math model errors. You will work closely with our product managers and software engineers to disambiguate complex supply chain problems and create ML solutions to solve those problems at scale. You will directly impact our direct customers, and even play with big data and incredible scale in the background. Watch http://bit.ly/amazon-scot to get the big picture. Key job responsibilities As part of your daily work you will: * Design, development and evaluation of highly innovative OR/ML models for solving complex business problems. * Analyze and extract relevant information from large amounts of data to help automate and optimize key processes. * Research and apply the latest ML techniques and best practices from both academia and industry. * Think about customers and how to improve the customer delivery experience. * Use and analytical techniques to create scalable solutions for business problems. * Work closely with data & software engineering teams to build model implementations and integrate successful models and algorithms in production systems at very large scale. * Technically lead and mentor other scientists in team. * Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation. A day in the life This is a great role for someone who likes to learn new things. You will have the opportunity to learn all about how Amazon plans for and executes within it's logistics network including Fulfillment Centers, Sort Centers, Delivery Stations, and more. In this role, you will be a design and develop Optimization and Machine Learning models with significant scope, impact, and high visibility. Your solutions will impact business segments worth many-billions-of-dollars and geographies spanning multiple countries and markets. From day one, you will be working with bar raising scientists, engineers, and designers. You will also collaborate with the broader science community in Amazon to broaden the horizon of your work. Successful candidates must thrive in fast-paced environments, which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon's strategic needs. We look for individuals who know how to deliver results and show a desire to develop themselves, their colleagues, and their career. About the team Network Planning and Fulfillment Execution Science team contains a group of scientists with different technical backgrounds including Machine Learning and Operations Research, who will collaborate closely with you on your projects. Our team directly supports multiple functional areas across Fulfillment Optimization and the research needs of the corresponding product and engineering teams. We tackle some of the most mathematically complex challenges in facility and transportation planning to improve Amazon's operational efficiency worldwide and at a scale that is unique to Amazon. We often seek the opportunity of applying hybrid techniques in the space of Operations Research and Machine Learning to tackle some of our biggest technical challenges. We disambiguate complex supply chain problems and create ML and optimization solutions to solve those problems at scale. We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA
April 29, 2021Amazon Scholar Aravind Srinivasan on the importance of machine learning for real-time and offline resource management.
