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Senior Data Scientist, Pricing Science, Data, and Insights

Amazon

Amazon

Data Science
Seattle, WA, USA
Posted on Mar 11, 2026

Description

Are you looking for a role where you have the opportunity to shape Amazon’s Pricing and using data science, analytics, and insights? If so, our role in Amazon's Pricing organization is for you. Amazon's Pricing Analytics organization is seeking a highly analytical Senior Data Scientist.

In this role, you will build and and delivers analytical solutions through agentic AI, insights, scientific studies, analyses, anomaly detection tools and technologies, which will deliver the best prices and experiences to our customers. Data science and analytics is at the core of Amazon’s culture, and your work will have a direct impact on decision making and strategy for the Pricing organization. This role requires a self-starting leader with high judgment that thrives in ambiguity and inspires their team. We are looking for an experienced data scientist with broad and deep scientific and analytical abilities, that is customer and delivery-focused, and a has a track record of earning your customers and peer’s trust.

To be successful in this role, you will need a successful track record of working on diverse data science projects, agentic AI solutions, strong business acumen, statistics, experimentation, and an entrepreneurial mindset.

Key job responsibilities
- Build Agentic AI solutions within the pricing analytics organization
- Mentor and grow other scientists and BIEs
- Develop, build, and deliver scientific and analytical data science solutions, models, and business strategy.
- Lead modeling and experimentation, deep dive analyses of business problems and formulate conclusions and recommendations to be presented to senior leadership as well as published literature.
- Leverage LLMs to deploy, automate, and generate Insights and drive growth discussions with Product teams.
- Produce written scientific recommendations and insights for key stakeholders that will help shape effective metric development and reporting.
- Continuously invent, simplify, and automate your team’s products, tools, services, and methodologies. Improving back-end data sources and models for increased accuracy and simplicity.
- Recognize and adopt the best practices in data science, reporting, analyses, data quality, and modeling.