As a Senior Applied Scientist in the Product Intelligence team, you will lead the development of advanced science solutions to better represent, model, predict and understand the inter-relation between product features, price signals, and price competitiveness.
Your work will leverage the latest in Deep Learning, Active Learning, and Reinforcement Learning to enhance product understanding, and develop advanced explainability capabilities and price reasoning methods for a deeper understanding of products and pricing competitiveness.
You will also lead research projects to tackle pricing-related unsolved problems, mentor interns, and author academic papers to summarize your findings for external publication.
This high-impact role is critical to our core business, influencing the reliability of information for billions of products on Amazon's platform, and impacting the shopping journey for hundreds of millions of customers. The systems you build will be used to monitor Amazon's entire product selection to ensure their quality, the availability of accurate price distributions, and more.
We seek an experienced scientist with deep knowledge of ML, DL, RL, and GenAI. The role will also require cross-functional collaboration skills, and staying up to date with the latest advancements in Generative AI, model explainability, quantile-regression models, etc.
Key job responsibilities
Implement and deploy systems that leverage ML, DL, RL and other techniques to address some of hardest problems in the pricing space.
Set scientific standards and see the big picture to influence Amazon's long-term vision for retail pricing science.
Work cross-functionally with various teams to align machine learning initiatives with business goals and execute them successfully.
Lead research projects and participate in the publication of external academic papers at top conferences and journals.
About the team
Within Pricing & Promotions Science, the Product Intelligence team leverages billion-scale multi-modal data on billions of Amazon and external competitor products to build advanced machine learning models for product similarity, substitutability, error detection & correction, and probabilistic price estimation. We preserve long term customer trust by ensuring Amazon's prices are always competitive and error free.- 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- 5+ years of building machine learning models for business application experience
- 5+ years of industry or academic research experience
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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 for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location 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. For more information, please visit
https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
