Amazon's Pricing & Promotions Science is seeking a driven Sr. 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 on billions of Amazon and Third Party Seller products worldwide.
We are looking for a talented, organized, and customer-focused Science lead to join our Pricing and Promotions Optimization science group, with a charter to measure, refine, and launch customer-obsessed improvements to our algorithmic pricing and promotion models across all products listed on Amazon.
This is a high-opportunity, high-ambiguity space and requires an individual with exceptional machine learning modeling expertise, excellent cross-functional collaboration skills, business acumen and an entrepreneurial spirit. We are looking for a clear thinking self-starter, who is comfortable with ambiguity, demonstrates strong attention to detail, and has the ability to work in a fast-paced and high-leverage environment.
Key job responsibilities
- See the big picture. Understand and influence the long term vision for Amazon's science-based competitive, perception-preserving pricing techniques
- Build strong collaborations. Partner with product, engineering, and science teams within P2 to deploy machine learning price estimation and error correction solutions at Amazon scale
- Stay informed. Establish mechanisms to stay up to date on latest scientific advancements in machine learning, neural networks, natural language processing, probabilistic forecasting, 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 technical machine learning expertise to incrementally move the needle on some of our hardest pricing problems.
About the team
The P2 Optimization team owns price quality, discovery and optimization initiatives, including criteria for price matching, price setting, internal price discovery within partner surfaces (e.g. search), pricing bandits, and Promotion type optimization.
We leverage planet scale data on billions of Amazon and external competitor products to build advanced optimization models for pricing, elasticity estimation, product substitutability, and optimization. We preserve long term customer trust by ensuring Amazon's prices are always competitive and error free.
