Amazon's Pricing & Promotions Optimization Science is seeking a motivated Applied Scientist to harness planet scale multi-modal datasets, and navigate a continuously evolving competitor landscape, in order to regularly generate fresh customer-relevant prices and promotions on billions of Amazon and Third Party Seller products worldwide.
We are looking for a talented, organized, and customer-focused applied scientists to define, measure, and launch customer-obsessed solutions across all products listed on Amazon.
This role requires an individual with exceptional AI and data science expertise, excellent cross-functional collaboration skills, strong business acumen, and an entrepreneurial spirit. We are looking for an experienced innovator, who is a self-starter, comfortable with ambiguity, demonstrates strong attention to detail, and has the ability to work in a fast-paced and ever-changing environment.
Key job responsibilities
- See the big picture. Understand and influence the long term vision for Amazon's science-based competitive, perception-preserving pricing/promotion techniques
- Build strong collaborations. Partner with product, engineering, and science teams within and outside Pricing & Promotions org to deploy AI/Data solutions at Amazon scale
- Stay informed. Establish mechanisms to stay up to date on latest scientific advancements in neural networks, search & ranking, natural language processing, probabilistic forecasting, reinforcement learning, and multi-objective optimization techniques. Identify opportunities to apply them to relevant Pricing & Promotions business problems
- Keep innovating for our customers. Foster an environment that promotes rapid experimentation, continuous learning, and incremental value delivery
- Successfully execute & deliver. Apply your exceptional AI and data science expertise to incrementally move the needle on some of our hardest science and tech problems
About the team
About the team: the Pricing and Promotion Optimization team within P2 Science leads the definition, measurement, and implementation of the state-of-the-art AI and data science solutions to improve price/promotion quality across the site and bring value to customers, sellers and Amazon.
We are looking for a talented, organized, and customer-focused applied scientists to define, measure, and launch customer-obsessed solutions across all products listed on Amazon.
This role requires an individual with exceptional AI and data science expertise, excellent cross-functional collaboration skills, strong business acumen, and an entrepreneurial spirit. We are looking for an experienced innovator, who is a self-starter, comfortable with ambiguity, demonstrates strong attention to detail, and has the ability to work in a fast-paced and ever-changing environment.
Key job responsibilities
- See the big picture. Understand and influence the long term vision for Amazon's science-based competitive, perception-preserving pricing/promotion techniques
- Build strong collaborations. Partner with product, engineering, and science teams within and outside Pricing & Promotions org to deploy AI/Data solutions at Amazon scale
- Stay informed. Establish mechanisms to stay up to date on latest scientific advancements in neural networks, search & ranking, natural language processing, probabilistic forecasting, reinforcement learning, and multi-objective optimization techniques. Identify opportunities to apply them to relevant Pricing & Promotions business problems
- Keep innovating for our customers. Foster an environment that promotes rapid experimentation, continuous learning, and incremental value delivery
- Successfully execute & deliver. Apply your exceptional AI and data science expertise to incrementally move the needle on some of our hardest science and tech problems
About the team
About the team: the Pricing and Promotion Optimization team within P2 Science leads the definition, measurement, and implementation of the state-of-the-art AI and data science solutions to improve price/promotion quality across the site and bring value to customers, sellers and Amazon.