Amazon
Senior Applied Scientist, Worldwide Defect Elimination
Amazon, Seattle, Washington, us, 98127
Job ID: 2777910 | Amazon.com Services LLCAs a Senior Applied Scientist in Worldwide Defect Elimination - Amazon Stores Customer Service (ASCS) at Amazon, your role is pivotal in leveraging statistics/machine learning (ML) techniques to address customer issues at scale. You'll lead the development of innovative solutions that use causal inference to drive business decisions. You will utilize the latest in ML to comb over our billions of contacts (using a combination of media). You will lead the development of the production design and implementation of your science models. As a part of this role, you will collaborate with a large team of experts in the field (including economists) and move the state of research forward.Key job responsibilities
Research and Development of Cutting-Edge Modeling techniques for statistics / ML and causal inference.Establishing scientific culture and standards for all the scientists (publication, best practices, reviews, etc.)Delivering solutions to the core business problems above and influencing business partnersDevelop scientific talent on the teamA day in the life
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!BASIC QUALIFICATIONS
PhD, or Master's degree and 6+ years of applied research experience3+ years of building machine learning models for business application experienceExperience programming in Java, C++, Python or related languageExperience with neural deep learning methods and machine learningPREFERRED QUALIFICATIONS
Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.Experience with large scale distributed systems such as Hadoop, Spark etc.Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on 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 https://www.aboutamazon.com/workplace/employee-benefits.
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Research and Development of Cutting-Edge Modeling techniques for statistics / ML and causal inference.Establishing scientific culture and standards for all the scientists (publication, best practices, reviews, etc.)Delivering solutions to the core business problems above and influencing business partnersDevelop scientific talent on the teamA day in the life
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!BASIC QUALIFICATIONS
PhD, or Master's degree and 6+ years of applied research experience3+ years of building machine learning models for business application experienceExperience programming in Java, C++, Python or related languageExperience with neural deep learning methods and machine learningPREFERRED QUALIFICATIONS
Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.Experience with large scale distributed systems such as Hadoop, Spark etc.Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on 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 https://www.aboutamazon.com/workplace/employee-benefits.
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