Description Are you seeking an environment where you can drive innovation? Do you want to apply machine learning techniques and advanced statistical modeling to solve real world problems in one of the world’s largest Supply Chain Management systems? Do you want to play a crucial role in the future of Amazon's Consumer business? The Inbound Capacity team is part of Amazon’s Supply Chain Optimization Technology/Inbound Systems organization, and is responsible for optimizing the usage of storage and inbound capacity of Amazon’s fulfillment network to maximize the long term free cash flow for the company. We generate capacity control signals for Amazon’s automated supply chain system to ensure that their decisions always stay within the available capacity for each marketplace as well as the fulfillment centers supporting it. We achieve this objective using advanced science technologies in simulation, machine learning and optimization. As an Applied Scientist in the team, you will operate at the apex of multiple advanced Amazon systems, getting global visibility of how Amazon functions and serves our customers. Your curious mind will enable the creation of products that drive ever-greater automation, scalability and optimization of every aspect of capacity management at Amazon, removing cost and delivering speed of execution to thrill our customers. The impact of your work will be global, material and remarkable. We will develop new statistical and machine learning techniques in prediction, clustering, anomaly detection, learning based decision making, etc. Detailed responsibilities include but not limited to: Build ML models to predict production systems’ behaviors. Collaborate with our software team to create scalable production implementations for large-scale data pipeline. Develop an understanding of key business metrics/KPIs and providing clear, compelling analysis that shapes the direction of our business. Presenting research results to our internal research community. You will research and implement novel machine learning and statistical approaches. Your contributions will be seen and recognized broadly within the Amazon Retail organization, contributing to the Amazon research corpus and patent portfolio. Basic Qualifications - 5+ years of building machine learning models or developing algorithms for business application experience - PhD, or Master's degree and 5+ years of science, technology, engineering or related field experience - Experience applying theoretical models in an applied environment - Experience programming or scripting language like Python, Java, C or C+- Experience in investigating, designing, prototyping, and delivering new and innovative system solutions - Experience in patents or publications at top-tier peer-reviewed conferences or journals Preferred Qualifications - PhD in operations research, applied mathematics, theoretical computer science, or equivalent - 3+ years of hands-on predictive modeling and large data analysis experience - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing - Experience in supply chain domain Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.