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 Sr. Applied Scientist you will invent novel solutions and prototypes, and
directly contribute to bringing your ideas to life through production
implementation. Current research areas include entity resolution, agentic AI,
large language models, and product substitutes. 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.
- 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: - 3+ years of building machine learning models for
business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning Preferred
Qualifications: - Experience with modeling tools such as R, scikit-learn, Spark
MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
- Experience with large scale machine learning systems such as profiling and
debugging and understanding of system performance and scalability
Amazon is an equal opportunity employer and does not discriminate on the basis
of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our
customers. If you have a disability and need a workplace accommodation or
adjustment during the application and hiring process, including support for the
interview or onboarding process, please visit
https://amazon.jobs/content/en/how-we-hire/accommodations
[https://amazon.jobs/content/en/how-we-hire/accommodations] for more
information. If the country/region you’re applying in isn’t listed, please
contact your Recruiting Partner.
The base salary for this position ranges from $195,900/year up to $327,200/year.
Salary is based on a number of factors and may vary depending on job-related
knowledge, skills, and experience. Amazon is a total compensation company.
Dependent on the position offered, equity, sign-on payments, and other forms of
compensation may be provided as part of a total compensation package, in
addition to a full range of medical, financial, and/or other benefits.
Applicants should apply via our internal or external career site.
