Research Scientist



In this role you will help lead a large-scale modeling initiative that spans five global organizations and over twenty teams. You will model weather’s impact on business metrics and focus on the integration of how weather impacts Amazon’s network.

Your day-to-day will include model and algorithm development, experiment design, and deep dive analysis. You will learn current processes, build data backed solutions, educate diverse stakeholder groups, and audit implementation. You will work closely with our tech team to launch your solutions into production and build the metrics needed to monitor and improve their performance.

Amazon’s extensive logistics system is comprised of thousands of fixed infrastructure nodes, with millions of possible connections between them, and dozens of different transportation methods. Billions of packages flow through this network on a yearly basis, making the impact of optimal improvements unparalleled. This magnificent challenge is an opportunity to drive lasting impact in the design of one of the world’s most complex logistic systems and improve the experience of millions of customers every day. Come build with us!

A successful candidate in this position will be able to; communicate across diverse stakeholders, prioritize competing requests, and quantify decisions made. The ideal candidate will demonstrate deep understanding of statistical and machine learning concepts, a strong background in atmospheric science, and a high standard for coding best practices.

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:
· Master’s degree in Atmospheric Science, Data Science, Statistics or a related field.
· 5+ years industry experience in applying Machine Learning and/or statistics to problems in the Atmospheric Science space.
· Expert knowledge with a scripting language (e.g., Python).
· Experience with processing, analyzing, and modeling with weather data.
· Proficiency in the development, evaluation, implementation, and production launch of machine-learning algorithms and statistical models.
· 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.


In addition to those in basic qualifications, we are also ideally looking for someone who has:
· Ph.D. in Atmospheric Science, Data Science, Statistics or a related field.
· 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 Logistics/Supply Chain, or related Businesses.
· Familiar with spatial (GIS) modeling techniques.

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