Principal Applied Scientist
- Seattle, WA
The Optimal Inventory Health (OIH) team owns inventory health management worldwide across all Amazon businesses and formats including retail and FBA sellers. We use a dynamic programming model to maximize the net present value of inventory driving actions such as pricing markdowns, removals, and advertising.
We are looking for an industry-leading Scientist to join our team and shape the future of Amazon's Inventory Management strategies. You will also play an integral role in planning, modeling, and analysis that will maximize the long term value of inventory positions for Amazon and for Fulfillment by Amazon sellers. We use complex optimization and machine learning models built on Native AWS and SageMaker to maximize free cash flow for Amazon, driving actions such as website pricing markdowns, deal creation as well as driving customers to find the products they want at great prices through channels such as advertisements and the Amazon Outlet Store. Unlike other roles where the impact of your actions may not be easily visible, the impact of this role can be seen immediately on the Amazon website. The team is a highly leveraged team who utilizes experiments as a key way to innovate and drive value for customers.
The OIH Principal Scientist is responsible for building models to make critical decisions automatically, and working with the team to deploy world-wide solutions to solve complex inventory management challenges and support hundreds of millions of optimization calculation a week. You will evaluate and optimize inventory health for dozens of millions of products with different economics and demand patterns under different business programs to maximize inventory value. You will work closely with a world class research team, software engineers, and Amazon business teams worldwide to develop advanced mathematical and economic models and algorithms. You will also become an expert in supply chain management and retail pricing/marketing with deep understanding of Amazon business workflows and execution practices.
The ideal candidate is a motivated individual with strong skills in both robust, stochastic and combinatorial optimization with application to networks and/or with strong machine learning background including robotics and marketplace dynamical systems modeling. The qualified candidate will hold an advanced quantitative degree in the mathematical sciences, is comfortable with research methodologies and can tackle abstract business and engineering problems and deliver solutions at Amazon's breakneck pace.
• Graduate degree (MS or PhD) in Electrical Engineering, Computer Science, or Mathematics.
• More than 6 years of industrial/academic experience in data science, machine learning or a related field.
• Demonstrated use of modeling and optimization techniques tailored to meet business needs.
• Experience with leadership of experienced scientists as well as a record of developing junior members from academia/industry to a career track in a business environment.
• Familiar with programming languages such as C/C++, Java, Perl or Python
• PhD degree in Electrical Engineering, Computer Science, or Mathematics.
• More than 10 years of industrial/academic experience in building speech recognition and natural language processing systems (e.g. commercial speech products or government speech projects)
• Demonstrated experience to manage an industrial research team for at least 3 years.
• Excellent written and verbal communication skills
• Solid track record of thought leadership and contributions that have advanced the field
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