In the Amazon Selection Monitoring team, we want Amazon to have a complete awareness of all products on earth. We aggregate and identify all products along with complete and accurate facts. Our goal is to enrich and increase the coverage of Amazon product selection guided by consumers' interests. We are establishing the most comprehensive, accurate and fresh universal selection of products.
We have multiple position for applied scientists who are excited to work in big data challenges including; web scale data integration, entity and product matching, improving data quality, natural language processing, discovery of new relationships along with its sematic, knowledge inferencing and enhancement to support strategic and tactical decision-making.
We are looking for applied scientists with experience in building practical solutions and can work closely with software engineers to ship and automate solutions in production. Our applied scientist also collaborate and partner with other teams across Amazon to understand and reflect on how to create benefit for our customer.
Amazon Science gives you insight into the company's approach to customer-obsessed 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.
• 3+ years of hands-on experience in data integration, entity matching, data quality, NLP, or knowledge creation and processing.
• A strong interest and passion about data (the solutions and ideas are just means to get and produce good-useful data and knowledge)
• Master in Computer Science, Machine Learning, Data Quality, Statistics or a related field
• Algorithm development experience
• Experience mentoring and training others on complex technical issues
• PhD in Computer Science, Machine Learning, Data Quality, Statistics or a related field.
• Experience building systems and tools that perform large scale data analysis.
• Excellent communication and presentation skills.
• Experience with Java, Scala, Python.
• Experience with distributed data processing platforms such as Spark, MapReduce, and high-level query languages such as SQL, Hive, or Pig.
• Experience with ML packages and systems, deep learning, Tensor-Flow, SciKit, XGBoost ... etc.
Amazon is an Equal Opportunity-Affirmative Action Employer - Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation / Age.
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