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Machine Learning Scientist - Applied Science

Machine Learning Scientist - Applied Science

Job ID 
Posted Date 
Amazon Corporate LLC
Position Category 
Machine Learning Science
Recruiting Team 

Job Description

Join a high impact innovative team of scientists who use Machine Learning, NLP and Statistics to provide the best customer experience on the earth. Our team is building the next generation of intelligent customer service. Join us to build revolutionary products and change the way that people work with customer service. We are looking for versatile and passionate scientists who want to develop industry leading technologies and set the bar for every other company. We love data, and we have lots of it. We're looking for machine learning scientists to develop cutting edge machine learning, natural language understanding and statistical solutions.

As a machine learning scientist, you will work on a small team while collaborating with product and engineering teams. Your work will have a direct impact on the bottom line of our business while improving customer experience. If big data, cutting edge technologies and building intelligent systems excite you, if you love to innovate and deliver results, then we want you to be on our team.

Basic Qualifications

  • A PhD in Statistics, Computer Science Machine Learning, or in a highly quantitative field
  • 3+ years of hands-on experience in predictive modeling and big data analysis
  • 3+ years of experience using R/SAS and SQL in a Linux/UNIX environment
  • 3+ years of experience with Python
  • Strong communication and data presentation skills
  • Strong problem solving ability

Preferred Qualifications

  • 3+ years of industry experience in predictive modeling, machine learning and big data analysis
  • Strong skills with Python and Java/C++
  • 2+ year distributed programming experience

Keywords: Machine Learning, Applied Science, Natural Language Processing, NLP, NLU, apscijobs

Amazon is an Equal Opportunity-Affirmative Action Employer - Female/Minority/Disability/Veteran/Gender Identity/Sexual Orientation