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Job Field: Office Jobs
Location: SEATTLE, WA
Salary: $-
Job Type: Part Time

JOB SUMMARY:

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               <td align="left"><font style="font-size: 100%;">Research Scientist- Search (Natural Language processing, Optimization, Text Mining)<BR><BR><BR><BR>Job ID: 193781<BR>Location: US-WA-Seattle<BR><BR>Posted Date: 10/8/2012<BR>Company: Amazon Corporate LLC<BR><BR>Position Category: Research Science <BR>Apply for This Position<BR><BR>* Apply for this position online<BR>* E-mail this position to a friend<BR>Position Details<BR>Job Description<BR>Research Scientist- Amazon Search and Discovery<BR><BR>Amazon.com''s Search and Discovery team builds the systems and user interface to enable the fastest product discovery experience for Amazon desktop and mobile customers worldwide. We delight in data, and are constantly trying to make more informed decisions using advanced data mining techniques including prediction modeling, machine-learning, text-mining, and natural language processing. Our research scientist community is new, and we are looking for hands-on senior researchers to help us grow the team and drive data-based innovations.<BR><BR>About you:<BR>You''re a scientist looking for a career where you''ll be able to lead, to deliver, and to influence. You look at problems holistically, and thrive on the intricate complexity of designing multi-factor experiments and analyzing large quantities of data. You want to work on projects where you are implementing creative solutions to real problems and develop deep understanding of the problem space. You challenge yourself and others to constantly come up with better solutions. You''re a thought leader, and you back up your ideas with data. You want to create value and impact the direction of entire industries.<BR><BR>About us together:<BR>We''re going to change the way that customers search and discover products online. Along the way, we''re going to face seemingly impossible problems. We''re going to argue about how to solve them, and we''ll work together to find a solution that is superior to each of the proposals we came in with. We''ll make tough decisions, but we''ll all understand why. We''ll be the dream team.<BR><BR>Some problem spaces we''ll be working on:<BR>PREDICTION MODELS- There''s an almost overwhelming amount of data available, and we need to make use of it to build the best predictors of which features are likely to have an impact and which aren''t. We''re constantly testing out new features and accurate prediction saves us the cost of unneeded cycles of development and experimentation. You?ll need to be both an engineer and scientist - you?ll build the platforms to test and measure your hypotheses, iterate on your designs, and find innovative signals and solutions that fundamentally shift the effectiveness of our systems.<BR>CUSTOMER SEGMENTATION - As the earth?s most customer-centric company, we strive to understand our customers and anticipate their unique needs. We have a wealth of data already about the customers we interact with; what they''ve been shopping for, what they''ve recently purchased, etc. This data can be used to help us decide what else they are likely to be interested in and to respond to. Accessing this d                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           </font></td>
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