Applied Scientist, Pricing Science

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

Applied Scientist role focused on developing and launching customer-obsessed pricing algorithms for billions of products worldwide. This involves leveraging large-scale multi-modal datasets, applying machine learning, predictive modeling, causal inference, and reinforcement learning to optimize pricing strategies and tools for sellers. The role emphasizes collaboration with product and engineering teams, continuous learning, and delivering business impact through innovative pricing solutions.

What you'd actually do

  1. See the big picture. Understand and develop science to influence the long term vision for Amazon's science-based competitive, perception-preserving pricing techniques
  2. Build strong collaborations. Partner with product, engineering, and data teams within Pricing & Promotions to deploy models at Amazon scale
  3. Stay informed. Establish mechanisms to stay up to date on latest scientific advancements in machine learning, reinforcement learning, causal ML, and multi-objective optimization techniques. Identify opportunities to apply them to relevant Pricing & Promotions business problems
  4. Keep innovating for our customers. Foster an environment that promotes rapid experimentation, continuous learning, and incremental value delivery.
  5. Successfully execute & deliver. Apply your exceptional technical machine learning expertise to incrementally move the needle on some of our hardest pricing problems.

Skills

Required

  • 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
  • 2+ years of hands-on predictive modeling and large data analysis experience
  • Experience in solving business problems through machine learning, data mining and statistical algorithms

Nice to have

  • Experience building machine learning models or developing algorithms for business application
  • Experience in patents or publications at top-tier peer-reviewed conferences or journals
  • Experience with training and deploying machine learning systems to solve large-scale optimizations

What the JD emphasized

  • planet scale multi-modal datasets
  • customer-relevant prices on billions of Amazon products worldwide
  • exceptional machine learning and predictive modeling skills
  • causal and experimental evaluation experience
  • deploy models at Amazon scale
  • reinforcement learning
  • causal ML
  • multi-objective optimization techniques
  • invent and deliver price optimization, simulation, and competitiveness tools for Sellers
  • shape and extend our RL optimization platform
  • Promotion optimization initiatives
  • optimally price across systems and contexts
  • billions of Amazon and external competitor products
  • advanced optimization models for pricing, elasticity estimation, product substitutability, and optimization

Other signals

  • pricing optimization
  • machine learning
  • predictive modeling
  • reinforcement learning
  • causal ML
  • multi-objective optimization