Description Amazon's Optimal Inventory Health (OIH) org in Supply Chain Optimization (SCOT) group is looking for a Principal Applied Scientist to optimize one of the most complex eCommerce systems in the world. The Optimal Inventory Health (OIH) drives long-term cash flow (LTFCF) growth by determining optimal inventory dispositions under uncertainties in demand, pricing, and supply across Amazon’s 21 marketplaces global network. OIH is in the unique position within SCOT to drive the joint optimization across supply chain and marketing across the levers of Markdowns, Removals, Outlet, Deals, Sponsored Ads, and Paid Search etc. Our systems delivers hundreds of million dollar saving to Amazon each year. The Principal Applied Scientist will lead the science vision and implementation to optimize across inventory disposition channels and deliver best experience to Amazon customers through those levers. We are investing and building the next generation inventory disposition decision models based on cutting-edge technologies like Reinforcement learning, Causal inference, Deep Learning Prediction etc. Academic and/or practical background in Machine Learning and Operations Research are particularly relevant for this position. Experience in model-based engineering and/or multidisciplinary analysis & optimization is also a plus. 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 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. Key job responsibilities - Seek to understand in depth the end to end value chain of eCommerce across supply chain and marketing and identify areas of opportunities to grow our business using science solutions. - Lead science strategy and roadmap in OIH space - Drive alignment across organizations to achieve business goals - Lead/guide scientists and engineers across teams to develop, test, launch and improve of science models designed to optimize inventory value and customer experience. - Be responsible for communicating our innovations to the broader internal & external scientific community and business leadership. - Mentor and guide the applied scientists in our organization and hold us to a high standard of technical rigor and excellence in ML. A day in the life - You will engage with distinguished scientists and Senior Principal scientists across organizations to shape the vision of the eCommerce decision systems across supply chain and marketing. - You will collaborate with talented product managers and software engineers to build the end to end systems. - You will work with stakeholders across retail, supply chain, finance etc. to understand the business operation process and bottlenecks and build solution to provide the best experience to Amazon customers through automated OIH actions. - You have the access to the richest eCommerce data and will be able to see the actual significant business impact quickly with the models you build. About the team Supply Chain Optimization Technology (SCOT) is the core of the Amazon eCommerce business, which leverage science models and systems to automate the decisions and operations of the most complex supply chain in the world. Optimal Inventory Health (OIH) maximize the inventory value in Amazon through all the levers across traffic, marketing, pricing and reverse logistics. Basic Qualifications ▪ PhD in Multidisciplinary Design Optimization, Systems Optimization, Operations Research or related Engineering or Applied Sciences fields ▪ Previous work experience or demonstrated practical industry experience ▪ 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 of handling large dataset Preferred Qualifications ▪ PhD in Multidisciplinary Design Optimization, Systems Optimization, 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 (Matlab, R, etc.), and simulation software ▪ Exposure to relational databases and Linux 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 $179,000/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.