Are you excited by the idea of inventing new experiences on the most visited shopping page - amazon.com? Can you imagine saving millions of shoppers' time worldwide by presenting them with compelling products, services, and offers on Amazon homepage and product detail pages? Are you looking forward to solving challenging problems that blend business, scientific, and engineering disciplines? We work with billions of products and measure our impact in $'00 millions. Join us, be part of the shopping revolution, make history, and earn bragging rights!
Key job responsibilities
- Utilize artificial intelligence (includes Generative AI), causal inference, and creative problem-solving skills to improve one of the most significant ecommerce algorithms that impacts millions of shoppers and sellers in the planet.
- Partner closely with engineers to put your research and ideas into production on Amazon.com.
- Leverage your science expertise to research and deliver novel solutions to explore emerging problem spaces, and create or organize knowledge around them.
- Publish papers and file patents to contribute to the machine learning community.
- Present ideas to senior leadership (Sr. Managers and above) and mentor Applied Scientists and Engineers with an interest in artificial intelligence.
- Provide scientific consultation and influence teams beyond your immediate group, such as, Personalization, Media content teams, and Ads.
About the team
Buying Experience (BuyX) connects shoppers worldwide with the best product and offer evaluation experiences. Our Homepage guides customers to their next discovery—whether restocking essentials or exploring new Amazon services—through personalized, engaging content. On the Detail Page, we showcase products with tailored experiences across geographies and intents. Our team drives innovation through advanced algorithms, insightful product comparisons, dynamic content policies, and scalable architecture, ensuring every customer makes confident, informed decisions with each visit.
We are a team of Scientists, Economists, and Engineers, working together to realize this mission. We operate in a diverse space that includes modeling of customer purchase behavior, advanced simulation and experimentation. We employ a variety of AI/ML, and econometric techniques.- 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 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 in applied research
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 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.
