Applied Scientist Ii, Sponsored Products Marketplace Intelligence

Amazon Amazon · Big Tech · Seattle, WA · Applied Science

Applied Scientist II role at Amazon Ads focused on building production ML and bandit solutions to customize the Sponsored Products search experience. The role involves determining ad placement, quantity, and targeting using machine learning, causal inference, and optimization techniques. It emphasizes improving shopper discovery and advertiser reach by modeling shopper responses and optimizing ad allocation and ranking on the search page, with a recent focus on integrating LLMs/GenAI for production use cases.

What you'd actually do

  1. Develop real-time machine learning algorithms to allocate billions of ads per day in advertising auctions.
  2. Develop efficient algorithms for multi-objective optimization and AI control methods to find operating points for the ad marketplace then evolve them
  3. Perform hands-on analysis and modeling of enormous data sets to develop insights that improve shopper experience, without compromising Ad revenue in addition to designing metrics for complex systems.
  4. Drive end-to-end machine learning projects that have a high degree of ambiguity, scale, complexity.
  5. Run A/B experiments, gather data, and perform statistical analysis.

Skills

Required

  • 3+ years of building models for business application experience
  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
  • Experience programming in Java, C++, Python or related language
  • Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Nice to have

  • Experience using Unix/Linux
  • Experience in professional software development

What the JD emphasized

  • production ML
  • bandit solutions
  • LLMs / GenAI for production

Other signals

  • production ML
  • bandit solutions
  • online experimentation
  • causal modeling
  • LLMs / GenAI for production