Applied Scientist, Pricing Science

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

Applied Scientist role focused on developing and launching customer-obsessed improvements to pricing algorithms for billions of Amazon products, leveraging large-scale multi-modal datasets and predictive modeling, causal evaluation, and optimization techniques.

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

  • Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field
  • Experience programming in Java, C++, Python or related language
  • Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse

Nice to have

  • Experience implementing algorithms using both toolkits and self-developed code
  • Have publications at top-tier peer-reviewed conferences or journals

What the JD emphasized

  • exceptional machine learning and predictive modeling skills
  • causal and experimental evaluation experience
  • advanced optimization models

Other signals

  • pricing algorithms
  • predictive modeling
  • optimization models
  • machine learning