Data Scientist, Amazon Transportation Services

Job description

DESCRIPTION

The Line Haul Network Engineering and Product Development (LHNEPD) team, within Amazon Transportation Services (ATS), is looking for an exceptional, motivated, analytically minded data scientist with a strong delivery record to build statistical models and insights that will be the engine behind our products and services to optimize package flow, speed and efficiency in an already dynamic and fast-paced business.

You will have the opportunity to work across multiple problem spaces with a primary focus on models and insights that will redefine how we flow packages through the NA Middle Mile Network. You will be solving complex problems, working on difficult challenges in the data science space as the scale of our product portfolio grows. You will be responsible for generating new insights and recommendations to fuel new products and services features that will shape how the Middle Mile network evolves here at Amazon. You will simultaneously play an active role in translating business and functional requirements into concrete deliverables and working closely with the operations, product and software development teams to put solutions into production.

As a Data Scientist in the LHNEPD team, you will build and innovate within the Middle Mile network. You will work closely with business teams, technology teams and operations teams around the world, make a huge, measurable impact to Amazon’s customers, the retail and operations businesses, and build and innovate solutions that are simple and easy to maintain and scale. You are comfortable conversing with, collaborating with and persuading product, business and technology teams alike, and are poised and polished when presenting to senior level executives.

Want to learn more about what it's like working for Amazon Transportation Services? Check out this video! https://www.youtube.com/watch?v=en5YqrtBGvY&feature=youtu.be

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PREFERRED QUALIFICATIONS

· 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
· Master’s degree in quantitative field such as, Computer Science, Statistics, Mathematics, etc.
· Experience with processing, analyzing, and modeling with large data sets including GPS ping 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

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.

Desired profile

BASIC QUALIFICATIONS

· Bachelor’s degree in quantitative field such as Computer Science, Statistics, Mathematics, etc.
· 3+ years of relevant experience in Data Science/Data Warehousing/Business Intelligence/ Analytics
· 3+ years industry experience in applying Computer Science, Computer Engineering, Machine Learning, Statistics or related technical discipline
· 2+ years’ experience with Tableau, Looker or similar BI Reporting Platform
· Expert knowledge with a scripting language (e.g. Python, R) and with an object-oriented language (e.g. C++, Java).