The Technologies (SCOT) team is a powerhouse providing the brainpower behind the Amazon and using artificial intelligence to grow the most complex retail networks in the world.
The team is composed of scientists, engineers, and researchers who lead the industry in the development of innovative algorithms and strategies to maximize the long term effectiveness of Amazon’s Retail business.
This team works to extend existing and build new algorithms and systems to achieve an ideal position, maximizing in-stock selection on behalf of our customers and growing our Seller’s businesses. We own and operate production systems that effect the most optimal strategy to ship a customer order, simulation systems that allow internal customers experiment with what-if scenarios and analytical systems to help understand results and derive intelligence from the same.
The team in Bellevue, WA is focused on using cutting edge science to improve customer outcomes and transform our logistics, along with , and scalable distributed software in the cloud that automates and optimizes shipments to customers under the uncertainty of demand, and . When customers place orders, our systems use real time, large scale techniques to optimally choose from where to ship and how to consolidate multiple orders so that customers get their shipments on time or faster with the lowest possible costs.
As the Fulfillment Network Planning team, one of our core responsibilities is to leverage big data to identify key patterns of success and failure, identify the areas we need to focus on first, understand root cause(s) that triggered failure, and to build models that will help fix the most impactful problems. The amount of data, the variables that come into play, and diversity of customers and locations make this role very challenging and also fun. It's great for those who love solving problems, especially when dealing with a lot of ambiguity and asking lots of smart questions that will lead to the discovery of universal concepts, and truly innovative ML solutions that continuously improve the customer delivery experience. Every member of the team needs to have innovative thinking, a burning desire to learn, and the skills and experience needed to build science and technology so advanced that it will appear to generate “magical outcomes”.
As part of your daily work you will:
· Analyze and extract relevant information from large amounts of data to help automate and optimize key processes.
· Design, development and evaluation of highly innovative models for .
· Think about customers and how to improve the customer delivery experience
· Use and analytical techniques to create scalable solutions for business problems.
· Work closely with data & software engineering teams to build model implementations and integrate successful models and algorithms in production systems at very large scale.
· Technically lead and mentor other scientists in team.
· Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.
· Research and implement novel and statistical approaches.
To help describe some of our challenges, we created a short video about at Amazon - http://bit.ly/amazon-scot
· Ph.D. degree with 4+ years of applied research experience or a Master's degree and 6+ years of experience of applied research experience
· 3+ years of experience in building machine learning models for business application
· Experience programming in Java, C++, Python or related language
MS or PhD in Artificial Intelligence, Computer Science, Physics, Statistics, Applied Math, or Operations Research
· Ph.D. in Computer Science, Machine Learning, Statistics or a related quantitative field
· 7+ years of practical experience applying ML to solve complex problems in an applied environment
· Significant peer-reviewed scientific contributions in premier journals and conferences
· Strong CS fundamentals in data structures, problem solving, algorithm design and complexity analysis
· Experience with defining research and development practices in an applied environment
· Proven track record in technically leading and mentoring scientists
· Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.