Applied Scientist II, Amazon Selling Partner Trust & Store Integrity Science

Amazon

DESCRIPTION

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon maintain the integrity of its product catalog and elevate Amazon Selling Partners to be the most successful by preventing abuse? Are you excited by the prospect of creating state-of-the-art algorithms to solve real world problems in catalog management? Do you like to own end-to-end business problems/metrics and directly impact the quality and trustworthiness of Amazon's product listings? Do you enjoy collaborating in a diverse team environment?

If yes, then you may be a great fit to join the Amazon Catalog Abuse Detection and Prevention Team. We are looking for a talented scientist who is passionate about building advanced machine learning systems that help detect and prevent catalog abuse across millions of product listings every day and scale up our operation with automation.

Key job responsibilities

  • Use machine learning and statistical techniques to create scalable catalog abuse detection solutions that identify listing violations, selling partner integrity, and content manipulation
  • Innovate with the latest GenAI technology to build highly automated solutions for efficient catalog monitoring, content verification, and automated listing compliance
  • Design, develop and deploy end-to-end machine learning solutions in the Amazon production environment
  • Learn, explore and experiment with the latest machine learning advancements to protect selling partner trust and integrity

A day in the life

You'll be working closely with business partners and engineering teams to create end-to-end scalable machine learning solutions that address real-world problems. You will build scalable, efficient, and automated processes for large-scale data analyses, model development, model validation, and model implementation.

You will also be providing clear and compelling reports for your solutions and contributing to the ongoing innovation and knowledge-sharing that are central to the team's success.

BASIC QUALIFICATIONS

  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
  • 3+ years of building models for business application 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 in solving business problems through machine learning, data mining and statistical algorithms
  • Experience implementing algorithms using toolkits and self-developed code
  • 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 https://amazon.jobs/content/en/how-we-hire/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 https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.

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Confirmed 19 hours ago. Posted 14 days ago.

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