Sr. Applied Scientist, Inbound Placement Algorithms

Amazon • Bellevue, WA

11d

About The Position

The Inventory Planning and Control team is looking for an applied scientist to help build next generation models for supply chain systems in the Supply Chain Optimization Technology (SCOT) group. We own the systems that decide where to place hundreds of millions of units of inventory a week, globally, shaping Amazon’s cost structures and value proposition to the customer and ultimately maximizing Amazon’s long term free cash flow. The work is complex and important to Amazon. There are no textbook solutions to the problems we are solving and very few attempts have been made to solve at Amazon's scale, which necessitates deep analytical thinking to solve problems. As a Applied Scientist, you will work with other Scientists, Software Engineers, Product Managers and business teams to understand the current challenges in our inventory systems, map these challenges to scientific models, innovate solutions using techniques in Operations Research, Machine Learning, Statistics, and Optimization and pick the right tools to deploy these solutions at scale. You will be a part of shaping the future of inventory placement systems at Amazon. Your work will be visible to the business leaders in SCOT and will impact on how we serve our customers so that they get the right product at the right time.

Requirements

• 3+ years of building machine learning models for business application experience
• PhD, or Master's degree and 6+ years of applied research experience
• Experience programming in Java, C++, Python or related language
• Experience with neural deep learning methods and machine learning
• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
• Experience with large scale distributed systems such as Hadoop, Spark etc.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees