This position gives you an opportunity to build metrics that shape Amazon's catalog initiatives world wide. If that rings a bell and if you possess the confidence to navigate through early stage ambiguities, read on.
Amazon Selection and Catalog Systems (ASCS) builds the systems that host and run the world’s largest e-Commerce products catalog - it powers the online buying experience for customers worldwide so they can find, discover and buy anything they want. Amazon’s customers rely on the completeness, consistency and correctness of Amazon's product data to make well-informed purchase decisions. Improving the quality of product data is a continuous process. It requires data driven decisions on what product data changes simplify and improve the Customers’ experience.
Our team seeks a Sr. Applied Scientist with demonstrated experience in experimentation techniques. The ideal candidate combines acumen in data science and statistical modeling to grapple with challenges and guide decision-making at the highest levels. This is an opportunity to influence catalog quality improvements across Amazon.
Key job responsibilities
1. Build AI Agents to simulate customer behavior on Amazon stores.
2. Use the agentic AI simulations to accelerate catalog experiments
3. Use the agentic AI simulations to define and measure the customer experience quality metrics for Amazon's catalog.
4. Partner with Product Managers and Engineering to build and scale new customer experience metrics
5. Guide quality improvement programs by generating actionable insights
About the team
We enable teams across Amazon to run A/B experiments on product listings through Catalog Experimentation Program. Additionally, using experimentation and causal inference models, we build customer impact metrics for different experiences in Amazon stores world wide. We help Catalog data quality initiatives understand the customer impact of their work streams and influence their priorities to maximize customer benefits.
