Principal Scientist, Supply Chain Technology
- Seattle, WA
Supply Chain Optimization Technologies (SCOT) optimizes Amazon's global supply chain end-to-end and build systems to source and 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. Inbound Product and Tech (IPT) team is part of SCOT and owns the tools and workflows that enable Suppliers, Carriers and Amazon to move inventory from source into Amazon network.
We are looking for an industry-leading Research Scientist to join our team and shape the future of Amazon Inbound Supply Chain. Our vision is to create an accurate model of the constraints and control inbound flow in the network based on customer demand, thereby giving reliable predictability to suppliers, carriers and buying and planning systems to optimize replenishment, placement and transportation decisions. In this role, you will be building models on and consulting on the design of Amazon's inbound supply chain. Within that, you will take ownership over modeling business segments worth many-billions-of-dollars and geographies. There are teams of software engineers, business intelligence engineers, and other scientists to support building out models in detail, bringing them to production, and automating data ingestion. Given that the opportunity impacts whole of Amazon inbound flow, the person in this role will be the thought leader on optimization models and is expected to drive solutioning and consensus with multiple teams within and outside SCOT.
• Ph.D. in a field such as Operations Research, Statistics, Applied Mathematics, Computer Science, Physics, Engineering, Economics or a related field.
• 10+ years of industry experience
• 4+ years modeling supply chain related problems
• 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.
• A working knowledge of smooth and non-smooth optimization methods accompanied by associated expertise in the use of tools and the latest technology (e.g. CPLEX, Gurobi, XPRESS).
• The ability to implement models and tools through the use of high-level modeling languages (e.g. AMPL, Mosel, R, Matlab).
• Experience prototyping and developing software in traditional programming languages (C++, Java, Clojure, Python).
• Familiarity with SQL and experience with very large-scale data. The ability to manipulate data by writing scripts (Perl, Ruby, Groovy) is a plus.
• Experience with high-impact decisions (>$1B)
• Experience with machine learning and optimization in production
• Experience with fully automated machine training (e.g. automatic re-training, automatic testing)
• Experience with complex supply chains (>100 facilities, >1000 routes)
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