Principal Applied Scientist - Machine Learning
- Seattle, WA
DESCRIPTION
Have you ever ordered a product on Amazon and when that box with the smile arrives you wonder how it got to you so fast? Wondered where it came from and how much it would have cost Amazon? If so, Amazon's Supply Chain Optimization Technologies (SCOT) team is for you. We build systems to peer into the future and estimate the distribution of tens of millions of products every week to Amazon's warehouses in the most cost-effective way. When customers place orders, our systems use real time, large scale optimization techniques to optimally choose where to ship from and how to consolidate multiple orders so that customers get their shipments on time or faster with the lowest possible transportation costs. This team is focused on saving hundreds of millions of dollars using cutting edge science, machine learning, and scalable distributed software on the Cloud that automates and optimizes inventory and shipments to customers under the uncertainty of demand, pricing and supply.
Amazon's Supply Chain Optimization Technologies (SCOT) has started a new team, FBA Inventory Optimization also referred to as Fulfillment-by-amazon Automation and Optimization (FAO), to focus on driving long term free cash flow by automating and optimizing our third-party supply chain. The teams efforts will address the key challenges facing the worldwide FBA business, including 1) improving FBA inventory efficiency, 2) efficiently balancing the supply and demand of FBA 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. This is truly a unique problem space - optimizing for inventory in Amazon's pipeline when you don't control the process or own the inventory. Help us automate Fulfillment By Amazon (FBA) inventory management on a worldwide scale and build scalable new systems from the ground up!
BASIC QUALIFICATIONS
• Ph.D. in Machine Learning, Statistics, Applied Mathematics, Computer Science or a related field with publications in refereed academic journals
• 10+ 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. Ability to speak at a level appropriate for the audience. Experience applying these skills in both academic teaching environment and a business setting is a plus
• 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
PREFERRED QUALIFICATIONS
• Deep knowledge of probabilistic machine learning
• Experience with deep learning toolkits and frameworks
• Expert in more than one more major programming languages (C++, Java, or similar) and at least one scripting language (Perl, Python, or similar)
• Solid software development experience
• Algorithm and model development experience for large-scale applications
• Strong fundamentals in problem solving, algorithm design and complexity analysis
• Strong personal interest in learning, researching, and creating new technologies with high customer impact
• Experience with defining research and development practices in an applied environment
• Professional traits that are not unique to this position, but necessary for Amazon leaders: Exhibits excellent judgment; Has relentlessly high standards; Thinks strategically, but stays on top of tactical execution; Expects and requires innovation of her/his team; Thinks big and has convictions; Results oriented; Has the innate ability to inspire passion in others
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