• Data Scientist

    Location US-WA-Seattle
    Posted Date 3 weeks ago(08/01/2018 3:47 PM)
    Job ID
    Amazon.com Services, Inc.
  • Job Description

    *Must be enrolled at a university and plan to graduate before September 2019. Otherwise, please apply to the Data Scientist internship posting if you are graduating after September 2019, or to full-time non-university positions if you have graduated more than six months ago.*

    We are looking for motivated Data Scientists with excellent leadership skills, and the ability to develop, automate, and run analytical models of our systems. You will have strong modeling skills and is comfortable owning their own data and working from concept through to execution. This role will also build tools and support structures needed to analyze data, dive deep into data to resolve root cause of systems errors & changes, and present findings to business partners to drive improvements.

    Applicants have a demonstrated ability to manage medium-scale modeling projects, identify requirements and build methodology and tools that are statistically grounded. You will have experience collaborating across organizational boundaries.

    Basic Qualifications

    • In the process of obtaining or recently obtained an advanced degree (Ph.D. strongly preferred) in Math, Statistics, Computer Science,
    • Experience with statistical tools (e.g. R) and analysis, regression modeling and forecasting, time series analysis. Able to write SQL scripts for analysis and reporting ( SQL, MySQL)
    • Experience using one or more programming languages (e.g. Python, Java, C++, C#, Ruby)
    • Experience with big data: processing, filtering, and presenting large quantities (100K to Millions of rows) of data.

    Preferred Qualifications

    • Experience in machine-learning methodologies (e.g. supervised and unsupervised learning, deep learning etc.)
    • Experience with clustered data processing (e.g. Hadoop, Spark, Map-reduce, Hive)
    • Experience in communicating technically, at a level appropriate for the audience

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