DESCRIPTION

Does the thought of improving one of the world's most complex logistic systems inspire you? Are you excited to apply your strong quantitative expertise to solve complex and large-scale challenges? Are you fascinated by the interactions between operations and strategy? If so, then this position is for you! Amazon's Data Science team, within the Modeling and Optimization organization (MOP), is looking for a motivated individual with strong model, algorithm, and software development, and communication skills to join the effort in evolving the network we have today into the network we need tomorrow.

Amazon's extensive logistics system is comprised of thousands of fixed infrastructure nodes, with millions of possible connections between them. Billions of packages flow through this network on a yearly basis, making the impact of optimal improvements unparalleled. This magnificent challenge is a terrific opportunity to analyze Amazon's data. Come build with us!

In this role, your main focus will be to develop models, algorithms, simulations, and experiments that bridge operational needs with strategic vision. Your job will straddle day-to-day decisions and strategic vision. You will learn current processes, build data backed solutions, educate diverse stakeholder groups, automate solutions, launch your work to production, and audit implementation. A successful candidate in this position will have a background in communicating across significant differences, prioritizing competing requests, and quantifying decisions made. You will explore current processes and design novel applicable solutions. To accomplish this you will partner across teams to identify opportunities, define methodology, implement robust solutions, and communicate learnings to a variety of individuals. You will balance the tradeoffs between customer experience, network speed, and cost, to measurably improve the network in a 3 to 6-month timeframe while providing direction to strategic design.

The ideal candidate will demonstrate deep understanding of statistical and machine learning concepts, a high standard for coding best practices, passion for pushing the team to improve their standard practices, technical skills for leveraging analytical tools to solve large scale problems and designing tools when they don't exist, technical aptitude to remain abreast with related science technologies, leadership in charting new analytical courses, and excitement to use iterative approaches to tackle long-term challenges. The successful candidate will have good communication skills and ability to speak at a level appropriate for the audience, will collaborate effectively with fellow scientists, software development engineers, and product managers, and will deliver business value in a close partnership with many stakeholders from operations, finance, IT, research, and business leadership.
• Amazon offers competitive packages including comprehensive health care, 401(k), restricted stock units, growth potential and a challenging and exciting work environment.

Amazon is an Equal Opportunity Employer - Minority / Women / Disability / Veteran / Gender Identity / Sexual Orientation / Age.

BASIC QUALIFICATIONS

• Quantitative Master's degree; such as Computer Science, Computer Engineering, Machine Learning, Statistics, Mathematics, etc
• 4 years industry experience in applying Computer Science, Computer Engineering, Machine Learning, Statistics or related technical discipline.
• Expert knowledge with a scripting language (e.g. Python) and with a object-oriented language (e.g. C++, Java).
• Proficiency in the development, validation, implementation, and production launch of machine-learning algorithms and models.
• A passion for implementing coding best practices across a team.
• Deep appreciation for diversity of thought and a proponent for collaborative solutions.
• Ability to communicate technical concepts and solutions at a level appropriate for technical and non-technical audiences.

PREFERRED QUALIFICATIONS

In addition to those in basic qualifications, we would love to talk to you if you have any of the following:
• Ph.D. in quantitative field such as, Computer Science, Computer Engineering, Machine Learning, Statistics, Mathematics, etc
• Experience with processing, analyzing, and modeling with GPS and/or weather data
• Experience with agile/scrum methodologies and its benefits of keeping scientists on track and iteratively delivering results.
• Experience with big data: extraction, processing, filtering, and presenting large data quantities (100K to Millions of rows) via AWS technologies, SQL, and data pipelines
• Familiarity with utilizing a clustered distributed-data processing tool such as Hadoop, Spark, Dask, Map-reduce, and Hive
• Familiarity with Logistics/Supply Chain, or related Businesses.
• Background in experimental design