Job Description

Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Applied scientist at Amazon partner closely with senior management, business stakeholders, scientist and engineers to solve key business problems. You will work in a fast moving environment to solve business problems as a member of cross-functional team embedded within a business unit. You will be expected to apply prediction and optimization methodologies to large data sets, and to build scalable model production pipelines, and contribute to the design of automated systems around the company. Key job responsibilities The Applied Scientist will be responsible for developing solutions to better predict and optimize the inbound and outbound volumes/backlogs in Amazon's network world wide. This position requires complex analytical problem-solving, quickly approach large ambiguous problems, apply their technical knowledge to identify opportunities for further research and be able to build automated pipelines. Candidates must thrive in fast-paced environments which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon's strategic needs. About the team QuBIT Science (Midas team) is revolutionizing data-driven decision-making across Amazon's operations. We specialize in delivering swift, scientifically rigorous solutions that often fall outside the immediate scope of larger central science organizations. Applied scientists at Amazon partner closely with senior management, business stakeholders, scientist and engineers to solve key business problems. You will work in a fast moving environment to solve business problems as a member of cross-functional team embedded within a business unit. You will be expected to apply prediction and optimization methodologies to large data sets, and to build scalable model production pipelines, and contribute to the design of automated systems around the company.

• 2+ years of building models for business application experience
• PhD, or Master's degree and 2+ 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
• 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 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 . This position will remain posted until filled. Applicants should apply via our internal or external career site. #J-18808-Ljbffr Jobleads-US

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