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Amazon

Applied Scientist, NAS Mosaic

Amazon, Seattle, Washington, United States, 98101

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Applied Scientist Position

Are you passionate about solving unique customer-facing problems on a large scale? Are you excited by developing and productizing machine learning, deep learning algorithms, and leveraging tons of Amazon data to learn and infer customer shopping patterns? Do you enjoy working with a diversity of engineers, machine learning scientists, product managers, and user-experience designers? If so, you have found the right match! Fashion is extremely fast-moving, visual, subjective, and it presents numerous unique problem domains such as product recommendations, product discovery, and evaluation. The vision for Amazon Fashion is to make Amazon the number one online shopping destination for fashion customers by providing large selections, inspiring and accurate recommendations, and a customer experience. The mission of the Size/Fit science team as part of Fashion Tech is to innovate and develop scalable ML solutions to provide personalized size and fit recommendations when Amazon Fashion customers evaluate apparel or shoes online. The team is hiring an experienced Applied Scientist who has a solid background in applied Machine Learning, including computer vision, recommendation systems, and generative AI. Key Job Responsibilities

Work on our Science team and partner closely with other scientists, data engineers, as well as product managers, UX designers, and business partners to answer complex problems with novel scientific approaches. Navigate ambiguous problems by working backward from customer needs to propose and develop effective scientific solutions. Have excellent communication skills to work with cross-functional team members to understand key questions and earn the trust of senior leaders. Be able to multi-task between different tasks such as gap analysis of algorithm results, integrating multiple disparate datasets, doing business intelligence, analyzing engagement metrics, or presenting to stakeholders. Thrive in an agile and fast-paced environment on highly visible projects and initiatives. Basic Qualifications

3+ years of building models for business application experience PhD, or Master's degree and 4+ years of CS, CE, ML, or related field experience Experience in patents or publications at top-tier peer-reviewed conferences or journals 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, high-performance computing Preferred Qualifications

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

Amazon Accommodations

for more information. If the country/region you're applying in isn't 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 $136,000/year in our lowest geographic market up to $223,400/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

Amazon Benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.