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Amazon SCOT employees participate in innovation and diversity panel discussion

Watch the replay of the October 28 discussion featuring four Amazon leaders.

By Staff writer
November 01, 2021
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Amazon was a Diamond sponsor of INFORMS 2021, an annual meeting that connects more than 7,000 students, academic and industry experts in fields including operations research, analytics, management science, economics, behavioral science, statistics, artificial intelligence, data science, applied mathematics, and other research fields.

During the conference, members from Amazon's Supply Chain Optimization and Technologies (SCOT) team held a virtual panel discussion on innovation and diversity at the company, moderated by Alexandra Jovicic, senior manager of software development.

Panelists included:

  • Ilse Debruin, director of global logistics
  • Juan Huerta, senior manager of research science
  • Julian Pachon, director or Last Mile science
  • Stephanie Collett, director of sourcing
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US, NY, New York
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Applied Scientist, Generative Artificial Intelligence (AI) Innovation Center
AU, NSW, Sydney
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US, NY, New York
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Applied Scientist , Sponsored Products Ads Response Prediction
US, WA, Seattle
** This position is open to all candidates in Palo Alto, CA, Seattle, WA, NYC and Arlington, VA ** Amazon Ads Response Prediction team is your choice, if you want to join a highly motivated, collaborative, and fun-loving team with a strong entrepreneurial spirit and bias for action. We are seeking an experienced and motivated Machine Learning Applied Scientist who loves to innovate at the intersection of customer experience, deep learning, and high-scale machine-learning systems. Amazon Advertising operates at the intersection of eCommerce and advertising, and is investing heavily in building a world-class advertising business. We are defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products to improve both shopper and advertiser experience. With a broad mandate to experiment and innovate, we grow at an unprecedented rate with a seemingly endless range of new opportunities. We are looking for a talented Machine Learning Applied Scientist for our Amazon Ads Response Prediction team to grow the business. We are providing advanced real-time machine learning services to connect shoppers with right ads on all platforms and surfaces worldwide. Through the deep understanding of both shoppers and products, we help shoppers discover new products they love, be the most efficient way for advertisers to meet their customers, and helps Amazon continuously innovate on behalf of all customers. Key job responsibilities As a Machine Learning Applied Scientist, you will: * Conduct deep data analysis to derive insights to the business, and identify gaps and new opportunities * Develop scalable and effective machine-learning models and optimization strategies to solve business problems * Run regular A/B experiments, gather data, and perform statistical analysis * Work closely with software engineers to deliver end-to-end solutions into production * Improve the scalability, efficiency and automation of large-scale data analytics, model training, deployment and serving * Conduct research on new machine-learning modeling to optimize all aspects of Sponsored Products business About the team We are pioneers in applying advanced machine learning and generative AI algorithms in Sponsored Products business. We empower every customer with a customized discovery experiences from back-end optimization (such as customized response prediction models) to front-end CX innovation (such as widgets), to help shoppers feel understood and shop efficiently on and off Amazon.
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