drjobs Applied Scientist Amazon

Applied Scientist Amazon

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1 Vacancy
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Job Location drjobs

New York City, NY - USA

Yearly Salary drjobs

$ 136000 - 223400

Vacancy

1 Vacancy

Job Description

Amazon Advertising operates at the intersection of eCommerce and advertising and is investing heavily in building a worldclass advertising business. We are defining and delivering a collection of selfservice performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving longterm growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create worldclass products to improve both shopper and advertiser experience. With a broad mandate to experiment and innovate we grow at an unprecedented rate with a seemingly endless range of new opportunities.

The Ad Response Prediction team in Sponsored Products organization build advanced deeplearning models largescale machinelearning pipelines and realtime serving infra to match shoppers intent to relevant ads on all devices for all contexts and in all marketplaces. Through precise estimation of shoppers interaction with ads and their longterm value we aim to drive optimal ads allocation and pricing and help to deliver a relevant engaging and delightful ads experience to Amazon shoppers. As the business and the complexity of various new initiatives we take continues to grow we are looking for talented Applied Scientists to join the team.

Key job responsibilities
As a Applied Scientist II you will:

* Conduct handson data analysis build largescale machinelearning models and pipelines
* Work closely with software engineers on detailed requirements technical designs and implementation of endtoend solutions in production
* Run regular A/B experiments gather data perform statistical analysis and communicate the impact to senior management
* Establish scalable efficient automated processes for largescale data analysis machinelearning model development model validation and serving
* Provide technical leadership research new machine learning approaches to drive continued scientific innovation
* Be a member of the Amazonwide Machine Learning Community participating in internal and external MeetUps Hackathons and Conferences

3 years of building models for business application experience
PhD or Masters degree and 4 years of CS CE ML or related field experience
Experience programming in Java C Python or related language
Experience in any of the following areas: algorithms and data structures parsing numerical optimization data mining parallel and distributed computing highperformance computing

Experience using Unix/Linux
Experience in professional software development

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136000/year in our lowest geographic market up to $223400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on jobrelated knowledge skills and experience. Amazon is a total compensation company. Dependent on the position offered equity signon payments and other forms of compensation may be provided as part of a total compensation package in addition to a full range of medical financial and/or other benefits. For more information please visit
This position will remain posted until filled. Applicants should apply via our internal or external career site.

Employment Type

Full-Time

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