Data Scientist II, Amazon Private Brands, PBI Selection Guidance

Saved job description

Join our Amazon Private Brands Selection Guidance organization in building science and tech solutions at scale to delight our customers with products across our leading private brands such as Amazon Basics, Amazon Essentials, and by Amazon.

The Selection Guidance team applies Generative AI, Machine Learning, Statistics, and Economics solutions to drive our private brands product assortment, strategic business decisions, and product inputs such as title, price, merchandising and ordering. We are an interdisciplinary team of Scientists, Economists, Engineers, and Product Managers incubating and building day one solutions using novel technology, to solve some of the toughest business problems at Amazon.

As a Data Scientist you will investigate business problems using data, invent novel solutions and prototypes, and directly contribute to bringing your ideas to life through production implementation. Current research areas include named entity recognition, product substitutes, pricing optimization, agentic AI, and large language models. You will review and guide scientists across the team on their designs and implementations, and raise the team bar for science research and prototypes.

This is a unique, high visibility opportunity for someone who wants to develop ambitious science solutions and have direct business and customer impact.

Key job responsibilities

Partner with business stakeholders to deeply understand APB business problems and frame ambiguous business problems as science problems and solutions.

Perform data analysis and build data pipelines to drive business decisions.

Invent novel science solutions, develop prototypes, and deploy production software to solve business problems.

Review and guide science solutions across the team.

Publish and socialize your and the team's research across Amazon and external avenues as appropriate

Leverage industry best practices to establish repeatable applied science practices, principles & processes.

Requirements: - 2+ years of data scientist experience

- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience

- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience

- 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience

- Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)

- Experience applying theoretical models in an applied environment