Applied Scientist II, Amazon Private Brands

Applied Scientist II, Amazon Private Brands

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 an Applied Scientist you apply state-of-the‑art research to business problems, 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 development. 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.
• Adapt and apply state-of-the‑art machine learning solutions to business problems.
• 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.

Basic Qualifications

• PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience.
• 3+ years of building models for business application experience.
• Experience in patents or publications at top‑tier peer‑reviewed conferences or journals.
• Experience programming in Java, C++, Python or related language.
• Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high‑performance computing.

Preferred Qualifications

• PhD in computer science, machine learning, engineering, or related fields.
• Experience building machine learning models or developing algorithms for business application.
• Experience in professional software development.
• Experience applying theoretical models in an applied environment.
• Experience using Unix/Linux.
• Usage of generative AI tools to enhance workflow efficiency, with a willingness to learn effective prompting and evaluation practices.
• Ability to recognize opportunities where generative AI could enhance products, workflows, or customer experiences.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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