Applied Scientist

Seattle, Washington, USA

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Amazon.com

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Job summary
Amazon Science gives you insight into the company’s approach to customer focused scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work.

Please visit https://www.amazon.science for more information.

Are you interested in helping Amazon ensure that customers make great purchase decisions and that the world's most recognized Brands using Amazon are successful listing and selling their products? The Brand Protection team designs and builds high performance software systems using machine learning that identify and prevent abuse on behalf of brand owners worldwide.

We are looking for a highly talented scientist to help build of our vision for Brand Protection. As a applied scientist on the team, you will interface directly with Product and Engineer to build hands of the wheel solutions to identify risks and abusive behaviour to protect legit brands in our catalog. You will work backwards from data insights and customer feedback to build the right machine learning solutions, and resourceful in finding innovative solutions to unsolved problems.

This is a global role that will include interaction with Brands, Sellers and internal teams, requiring a strong ability to communicate effectively and understand the different needs of global customers. You should have extensive experience driving Machine Learning initiatives, from conception to launch in a rapidly evolving environment. Amazon’s growth requires leaders who move fast, have an entrepreneurial spirit to create new solutions, have an unrelenting tenacity to get things done, and are capable of breaking down and solving complex problems.

Major responsibilities:
  • Understand business challenges by analyzing data and customer feedback
  • Collaborate with tech and product teams on building ML strategies, experimentation, implementation and continuous improvement
  • Analyze and extract relevant information from large amounts of both structured and unstructured data to design strategies to solve business problems.
  • Use various machine learning techniques to create scalable solutions for business problems
  • Create business and analytics reports and present to the senior management teams
  • Research and implement novel machine learning and statistical approaches

Basic Qualifications


  • PhD or equivalent Master's Degree plus 4+ years of experience in CS, CE, ML or related field
  • Experience programming in Java, C++, Python or related language

  • 3+ year of hand-on modeling experience in a machine learning focused area
  • Deep understanding of statistical modeling and deep learning techniques.
  • Strong problem solving ability
  • Strong written and verbal communication skills and data presentation skills.
  • 3 year experience in Python and SQL


Preferred Qualifications

  • Modeling experience in Risk modeling, Abuse and Fraud Detection
  • Understanding of Software Development Life Cycle (SDLC) and project planning/execution skills including estimating and scheduling.
  • Ability and willingness to multi-task and learn new technologies quickly.
  • Familiar with AWS machine learning technologies such as SageMaker.
  • Proficient with big data technologies such as spark



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.

Tags: AWS Big Data Deep Learning Machine Learning PhD Python Research SageMaker SDLC Spark SQL Statistical modeling Unstructured data

Perks/benefits: Career development Startup environment

Region: North America
Country: United States
Job stats:  2  1  0
Category: Data Science Jobs

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