The Fulfillment by Amazon (FBA) team is looking for a passionate, curious, and creative Research Scientist, with expertise and experience in operations research, operations management, supply chains, and revenue management, to join our top-notch cross-domain FBA science team. As a research scientist you will be responsible for designing and implementing cutting edge optimization models and machine learning models and building automated inventory management system to solve key challenges facing the worldwide FBA Seller business, including 1) improving FBA Seller inventory efficiency, 2) efficiently balancing the supply and demand of FBA Seller capacity, 3) closing worldwide selection gap by enabling global selling profitability, and 4) driving out costs across the FBA supply chain to spin the flywheel. Unlike many companies who buy existing off-the-shelf planning systems, we are responsible for studying, designing, and building systems to suit Amazon’s needs. Our team members have an opportunity to be on the forefront of thought leadership by working on some of the most difficult problems in the industry with some of the best product managers, research scientists/statisticians/economists and software developers in the business. This role will work with other senior and principal scientists, and partner with engineering and product teams to integrate scientific work into production systems. Key job responsibilities • Interact with engineering, operations, science and business teams to develop an understanding and domain knowledge of processes, system structures, and business requirements • Apply domain knowledge and business judgment to identify opportunities and quantify the impact aligning research direction to business requirements and make the right judgment on research project prioritization • Develop scalable mathematical models to derive optimal or near-optimal solutions to existing and new inventory planning challenges • Create prototypes and simulations to test devised solutions • Advocate technical solutions to business stakeholders, engineering teams, as well as executive level decision makers • Work closely with engineers to integrate prototypes into production systems • Create policy evaluation methods to track the actual performance of devised solutions in production systems, identify areas with potential for improvement and work with internal teams to improve the solution with new features A day in the life As a Research Scientist, you will solve real world large inventory problems by analyzing large amounts of business data, defining new metrics and business cases, designing simulations and experiments, applying supply chain modeling techniques, creating optimization models, and collaborating with teammates in business, software, and research. The successful candidate has solid research experience in Operations Research preferably with focus on Operations Management or other closely related areas or in area of Machine Learning. He or she will lead the research where we are responsible for developing solutions to better manage and optimize worldwide FBA inventory capacity, while providing the best experience to our Sellers to growth their business. About the team Fulfillment by Amazon (FBA) is a service that allows sellers to outsource order fulfillment to Amazon, allowing sellers to leverage Amazon’s world-class facilities to provide customers Prime delivery promise. Sellers gain access to Prime members worldwide, see their sales lift, and are free to focus their time and resources on what they do best while Amazon manages fulfillment. Over the last several years, sellers have enjoyed strong business growth with FBA shipping more than half of all products offered by Amazon. FBA focuses on helping sellers with automating and optimizing the third-party supply chain. FBA sellers leverage Amazon’s expertise in machine learning, optimization, data analytics, econometrics, and market design to deliver the best inventory management experience to sellers. We work full-stack, from foundational backend systems to future-forward user interfaces. Our culture is centered on rapid prototyping, rigorous experimentation, and data-driven decision-making.
