• Ph.D. in Machine Learning, Statistics, Applied Mathematics, Computer Science or a related field with publications in refereed academic journals.
• 7+ years of experience in solving complicated machine learning problems.
• Solid Machine Learning background and familiar with standard machine learning and statistical learning techniques.
• Hands-on experience using Java, C++, or other programming language, as well as with R, Python or similar scripting language.
• Demonstrated ability to serve as a technical lead
• Excellent communication skills, both written and oral with both technical and business people.
• Excellent writing skills for presenting business cases and to document the models and analysis and present the results/conclusions in order to influence important decisions.

Job summary SCOT-FBA team is looking for a passionate, curious, and creative Principal Applied Scientist who is an applied machine learning expert with a proven record of solving customer-facing problems through scalable ML solutions to join our top-notch cross-domain science team. We want to learn FBA Seller behaviors, understand Seller experience through internal and external data, design best policies and incentives, and develop science products and services to help Sellers to improve their inventory efficiency and long-term value from both Amazon’s and sellers’ perspectives by using innovative and scalable science solutions based on interdisciplinary research of operations research, machine learning, market design, causal analysis, and data analytics. As a principal applied scientist, you will work on various science projects that draw from a range of fields such as supervised and unsupervised learning, recommendation systems, advanced statistical modeling, NLP, transfer learning, causal analysis, reinforcement learning and others on large datasets. The role has high visibility to senior Amazon business leaders and involves working with other scientists, and partnering with engineering and product teams to integrate these models into production systems. About the team Supply Chain Optimization Technologies (SCOT) optimizes Amazon’s global supply chain end to end and build systems to deliver billions of products to our customers’ doorsteps faster every year while saving hundreds of millions of dollars using science, machine learning, and scalable distributed software on the Cloud. FBA is an Amazon service for our marketplace third party sellers, where our sellers leverage our world-class facilities and provide customers Prime delivery promise on all their goods. In last few years, Sellers enjoyed strong growth using FBA shipping more than half of all products offered on Amazon. SCOT has launched a new team called Fulfillment by Amazon (FBA) to focus on automating and optimizing our third-party supply chain. The new organization is in charge of defining and delivering fulfillment services to our Sellers by leveraging Amazon’s expertise in machine learning, inventory optimization, big data, and distributed systems to deliver the best inventory management experiences for our FBA 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. 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.



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