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Senior Applied Scientist - Machine Learning Systems, Inc. - Palo Alto, CA

Job DescriptionAmazon Sponsored Ads is one of the fastest growing business domains and we are looking for talented scientists to join this team of incredible scientists to contribute to this growth. We are still in Day 1 and there is an abundance of opportunities that are yet to be explored. We are a team of highly motivated and collaborative team of applied scientists and engineers with an entrepreneurial spirit and bias for action. We have a broad mandate to experiment and innovate, and we are growing at an unprecedented rate with a seemingly endless range of new opportunities. Our systems and algorithms operate on one of the world's largest product catalogs, matching shoppers with advertised products with a high relevance bar and strict latency constraints. The ads sourcing works across the spectrum of ad serving including coverage expansion, increasing utilization of tail queries, ad relevance, ad quality, query understanding, and much more. Our technology enables thousands of brands, sellers and authors to drive discovery and sales of their products at Amazon by millions of customers. We are looking for Applied Scientists to explore the rich metadata source of Amazon to improve our understanding of the user query and their context. We ensure that we serve relevant ads to our customers that enhances both our end users shopping experience while helping our advertisers get the maximum ROI. You will be expected to demonstrate strong ownership and should be curious to learn and leverage the rich textual, image, and query level data to optimize for ad relevancy.This role will challenge you to utilize cutting-edge machine learning techniques in the domain of natural language processing (NLP), deep learning, and image recognition to deliver significant impact for the business. Ideal candidates will be able to work cross functionally across multiple stakeholders, synthesize the science needs of our business partners, develop models to solve business needs, and implement their solutions in production. Hence, we would expect them to be independent, have a natural bias to action, strong communicator, and be agile to make continuous incremental progress on a project without losing focus of the end goal.
Basic Qualifications

A BS/MS in Computer Science, Machine learning, Operational research, Statistics or similar quantitative field.
At least 5 years of hands-on experience building machine learning and/or natural language processing models
At least 5 years of experience in data mining and data analytics techniques.
At least 5 years experience in writing code in Java or C .
At least 5 years of experience using Perl or Python (or similar scripting language) for data processing and analytics.
At least 5 years of experience using R, Weka, Python, or other similar statistical software.

Preferred Qualifications

A PhD in Computer Science, Machine learning, Operational research, Statistics or similar quantitative field.
Published research work in academic conferences or industry circles
Comfortability with programming in SQL, Hive, Pig, R, Python, and familiarity/experience with AWS stack/tools.
Advertising technology experience (big plus).
Strong ability to solve ambiguous problems.
Able to clearly articulate complex models to technical and non-technical stakeholders, both written and verbal

51 days 5 hours ago, Inc.


Senior Applied Scientist - Machine Learning Systems, Inc. - Palo Alto, CA, United States


Location: Palo Alto, CA

Company Profile:
Amazon, a Fortune 500 company based in Seattle, Washington, is the global leader in e-commerce. Since Jeff Bezos started Amazon in 1995, we have significantly expanded our product offerings, international sites, and worldwide network of fulfillment and customer service centers. Today, Amazon offers everything from books and electronics to tennis rackets and diamond jewelry. We operate sites in Canada, China, France, Germany, Italy, Japan, Spain and United Kingdom and maintain dozens of fulfillment centers around the world which encompass more than 26 million square feet.