Description

　　Inventory Planning and Control (IPC) is seeking a Principal Applied Scientist to join its SPCB research team to help shape how Amazon supply chain optimizes inventory decisions in its global multi-tiered fulfillment network. SPCB research team owns the core decision models in the space of S&OP Planning, Placement, Capacity Control and Buying. Our models decide when, where, and how much we should buy, flow, and hold inventories in our global fulfillment network to meet Amazon’s business goals and to make our customers happy. We do this for hundreds of millions of items and hundreds of product lines worth billions of dollars of inventory world-wide for both our Retail and Seller business. Our systems are built entirely in-house, for which we constantly develop new technologies in automated inventory planning, prediction, optimization and simulation. Our systems operate at various scales, from real-time decision system that completes thousands of transactions per seconds, to large scale distributed system that optimizes the inventory decisions over millions of products simultaneously. Your tech solution will have large impacts to the physical supply chain of Amazon, and play a key role in improving Amazon consumer business’s long term profitability. You will work on some of the most difficult problems in the industry with some of the best product managers, scientists, and software engineers in the industry.

　　Key job responsibilities

　　As a Principal Applied Scientist in IPC, you will partner with the senior tech leaders in the organization to define the long term architecture of our decision optimization and prediction systems. You will play a key role in developing long term strategic solutions that have business impact beyond the scope of the organization. You will bring technical expertise in several technical areas of Operations Research or Machine Learning, and are able to help team to overcome key technical blockers. You will ensure senior leaders in the organization are up to speed on important trends, tools and technologies and how they will be used to impact the business. You are able to quickly approach large ambiguous problems, turn high-level business requirements into mathematical models, identify the right solution approach, and contribute to the software development for production systems. You will analyze large amounts of business data, define new metrics and business cases, design simulations and experiments, develop scientific, and collaborate with teammates in business, software, and research. 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.

　　A day in the life

　　S&OP Planning, Placement, Capacity Control and Buying (SPCB) space is at the center of Amazon’s supply chain. In this role, you will have opportunity to work with partners and stakeholders from Amazon’s retail, seller and operation departments worldwide. You will understand their challenges and pain points, and help develop solutions that improve how Amazon manages inventory in our global fulfillment network. To implement your solutions, you will work closely with our in-house product and engineering teams. Your work will have high visibility and impacts to Amazon’s business operation.

　　About the team

　　SPCB research team contains a large group of scientists with different technical backgrounds, who will collaborate closely with you on your projects. Our team directly supports 8 functional areas and the research needs of the corresponding engineering and product teams. We promote experimentation and learn by building. Our team constantly tackles some of the hardest modelling, optimization and prediction problems in inventory planning, optimization and control 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 are open to hiring candidates to work out of one of the following locations:

　　New York City, NY, USA | New York, NY, USA

　　Basic Qualifications

　　Ph.D. in Operations Research, Operations Management, Industrial Engineering, Statistics, Applied Mathematics, Computer Science or a related field.

　　7+ years of experience in solving complicated problems in the area of Operations Management or similar disciplines developing strategies for large-scale logistic networks.

　　7+ years of hands-on experience in building machine learning or optimization models in business environment.

　　Have production coding experience in one of the object-oriented programming languages such as Java, Python, C++, etc.

　　Proven track in leading, mentoring, and growing teams of scientists.

　　Preferred Qualifications

　　Have research/industrial experience of inventory/supply chain optimization.

　　Have experience working with simulation systems.

　　Have successful experience of applying hybrid techniques in the space of Machine Learning and Operations Research.

　　Excellent written and verbal communication skills with technical and business people; ability to speak at a level appropriate for the audience.

　　Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

　　Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $159,100/year in our lowest geographic market up to $309,400/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.