Sr Applied Scientist, Sponsored Products and Brands Ads Response Prediction

Amazon Amazon · Big Tech · Palo Alto, CA · Applied Science

This role focuses on developing and deploying machine learning models for Amazon's Sponsored Products and Brands Ads, aiming to improve customer experience and advertiser effectiveness. The scientist will conduct data analysis, build and optimize ML models, run A/B experiments, and collaborate with engineers to productionize solutions. They will also research new ML modeling techniques to enhance business outcomes.

What you'd actually do

  1. Conduct deep data analysis to derive insights to the business, and identify gaps and new opportunities
  2. Develop scalable and effective machine-learning models and optimization strategies to solve business problems
  3. Run regular A/B experiments, gather data, and perform statistical analysis
  4. Work closely with software engineers to deliver end-to-end solutions into production
  5. Improve the scalability, efficiency and automation of large-scale data analytics, model training, deployment and serving
  6. Conduct research on new machine-learning modeling to optimize all aspects of Sponsored Products and Brands business

Skills

Required

  • 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 with large scale distributed systems such as Hadoop, Spark etc.

What the JD emphasized

  • building machine learning models for business application experience
  • applied research experience
  • neural deep learning methods and machine learning

Other signals

  • develop scalable and effective machine-learning models
  • improve the scalability, efficiency and automation of large-scale data analytics, model training, deployment and serving
  • conduct research on new machine-learning modeling