Senior Applied Scientist, Sponsored Products and Brands

Amazon Amazon · Big Tech · NY +1 · Applied Science

Senior Applied Scientist role focused on leveraging generative AI and machine learning to re-imagine advertising experiences for Amazon Ads' Sponsored Products and Brands. The role involves leading ML efforts, analyzing large datasets, building and deploying ML models for insights, traffic monetization, and personalized shopping experiences, and driving end-to-end ML projects. It also includes running A/B experiments, establishing scalable processes, researching new ML approaches, and recruiting/mentoring other scientists.

What you'd actually do

  1. Be the technical leader in Machine Learning; lead efforts within this team and across other teams.
  2. Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience.
  3. Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity.
  4. Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models.
  5. Run A/B experiments, gather data, and perform statistical analysis.

Skills

Required

  • 3+ years of building machine learning models for business application experience
  • PhD, or Master's degree and 6+ years of applied research experience
  • Experience programming in Java, C++, Python or related language
  • Experience with neural deep learning methods and machine learning

Nice to have

  • Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
  • Experience in building machine learning models for business application

What the JD emphasized

  • building machine learning models for business application
  • end-to-end Machine Learning projects
  • machine learning models
  • scale, complexity
  • deploy your models into production

Other signals

  • Generative AI
  • Machine Learning
  • Personalized Shopping Experiences
  • Large-scale data analysis
  • End-to-end ML projects