Rarefied talent in data science, data technology, and analytics

Machine Learning Scientist


Job Description

What would you do if you had access to the world’s largest product catalog with billons of products, offers, images, customer reviews, search behavior, and much more? Amazon’s Search & Discovery group is looking for a Machine Learning scientist to analyze huge datasets using cloud computing and design scalable machine learning algorithms to build the world’s most complete, accurate and authoritative product catalog.

An information-rich and accurate product catalog is a critical strategic asset for Amazon. It powers unrivaled product discovery through search and recommendations, informs customers’ buying decisions, and positions Amazon as the first stop for our customers. An on-going research area is to understand how product data influences our customer’s shopping experience from discovery through checkout and post sales behavior. This is a challenging problem that requires creativity in both scalability and design of algorithms and experiments. In contrast to search relevance or ad placement we cannot directly measure the impact of changes with controlled experiments and need to estimate the latent variables from data signals. 

As a Research Scientist on this team you will be on the leading edge of understanding how information within Amazon’s catalog affects our customers and help devise short term and long term strategy for enhancing the catalog and customer experience. You will have the ability to influence how millions of customers discover and shop for products at Amazon within weeks of developing a new idea. You will have the opportunity to design new algorithmic solutions working at a scale rarely available elsewhere utilizing a vast array of Amazon’s cloud computingtechnologies such as EMR, SWF, Data Flow, RedShift and SQS, etc. 


  • Analyze large amounts of Amazon’s business data to discover patterns, find anomalies, build models and derive insight and business values.
  • Establish scalable, efficient, automated processes for large scale data analysis, model development, model validation and scoring.
  • Work closely with software engineering teams to integrate data analysis workflows in production system.
  • Proactively monitor and analyze complex systems to understand, diagnose and continuously improve business and operation parameters.
  • Produce compelling management reporting on a regular basis.
  • Participate in strategic analysis and help define the roadmap definition for the team.

Basic Qualifications

  • Master's degree in Computer Science (Machine learning, Data Mining), Mathematics (Statistics), Operations Research, or in a similar field.
  • Extensive knowledge and practical experience in machine learning, data mining, artificial intelligence, statistics with track record of publications.
  • Experience in building automated analytical systems utilizing large data sets.
  • Able to formulate complex SQL queries and experience working with BI and visualization tools.
  • Good knowledge of scientific programming in scripting languages like R/Python/Matlab.

Preferred Qualifications

  • PhD in Computer Science (Machine learning, Data Mining), Mathematics (Statistics), Operations Research, or in a similar field.
  • 2+ years of industry experience
  • Superior verbal and written communication skills, ability to convey rigorous mathematical concepts and considerations to non-experts
  • Object-oriented design and development in Java or C++.
  • Experience with distributed algorithms (Map-Reduce, MPI).
  • Results oriented person with a delivery focus.
  • Ability to handle multiple competing priorities in a fast-paced environment.
  • The ability to distill problem definitions, models, constraints from informal business requirements; and to deal with ambiguity and competing objectives.
  • Self-starter, inquisitive about data quality and their impact on Amazon customers.
Interested in this position?
Job Location
410 Terry Ave N
Seattle, WA 98109
Additional Job Details
Employment Type:
Full Time