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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%;">Machine Learning Scientist<BR><BR><BR><BR>Job ID: 190991<BR>Location: US-WA-Seattle<BR><BR>Posted Date: 9/27/2012<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>Amazon Fulfillment Services is looking for a motivated individual with strong analytical skills and practical experience to join our Modeling and Optimization team. We are hiring specialists at all levels into our scientific team with expertise in machine learning, network and combinatorial optimization, control theory, and/or numerical analysis.<BR>Amazon.com is a $48 billion dollar company that is growing rapidly. Because we are driven by faster delivery to customers, a more efficient supply chain network, and lower cost of operations, our main focus is in the development of analytical modeling and visualization tools fed by our massive amounts of available data. You will be responsible for building these analytical tools that improve the economics of the North American, European, and Japanese fulfillment networks as amazon increases the speed and decreases the cost to deliver product to customers. You will identify and evaluate opportunities to reduce variable costs by improving the fulfillment network topology, inventory placement, transportation operations and scheduling, fulfillment center processes, and the execution to operational plans. You will also improve the efficiency of capital investment by helping the fulfillment centers to improve storage utilization and the effective use of automation. Finally, you will help create the metrics to quantify improvements to the fulfillment costs (e.g., transportation and labor costs) resulting from the application of these optimization models and tools.<BR><BR>The ideal candidate will have the following machine learning experience and skills:<BR><BR><BR>* Ph.D. in Statistics, Applied Mathematics, Computer Science, Operations Research, or a related field with publications in refereed academic journals.<BR>* Good communication skills with both technical and business people. Ability to speak at a level appropriate for the audience.<BR>* Experience writing scripts (Perl, Ruby, Groovy) to manipulate data and developing software in traditional programming languages (C++, Java, Clojure, Python).<BR>* Experience implementing machine learning algorithms, tailored to particular business needs and tested on large datasets.<BR>* Familiarity in GIS, geocoding & computational geometry.<BR>* Familiarity with data visualization (e.g. R, ggplot, ggobi, Tableau).<BR>* Familiarity with forecasting and time series analysis.<BR>* Experience designing simulation and optimization models in for business decisions (e.g., staff scheduling, vehicle routing, and facility location) and/or feedback and/or predictive control.<BR>* The ability to implement models and tools through the use of high-level modeling languages (e.g. AMPL, Mosel, R, Matlab) is a plus.<BR>Basic Qualifications<BR><BR>* Mas                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      </font></td>
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