Amazon Scholars

This is a unique opportunity for a postdoc to work on research projects that investigate state of the art NLP, IR, and LLM approaches for understanding retail products and their pricing. This will include working with billion-scale datasets and investigating how the world knowledge captured by LLMs reflects real world prices, and investigating more advanced prompting and reasoning techniques to construct large knowledge graphs that are specialized for various pricing use cases such as probabilistic price estimation, as well as error detection and correction.Key job responsibilitiesIn this role you will:• Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community.• Publish your innovation in top-tier academic venues and hone your presentation skills.• Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise. About the teamThe retail pricing science team is a centralized diverse team of STEM scientists that develop statistical, ML, RL, optimization and economic models that drive pricing for products sold by Amazon worldwide, as well as monitoring of prices and experimentations in pricing. The team has a dual focus on competitiveness and long term financial optimality.Basic qualifications include: - PhD in a relevant field, received within 2 years of starting the program- Proven publication record in Operation Research, Management Science, Statistics, Machine Learning, Computer Science, Econ, or other related technical fields- Experience in data science and quantitative research- Proficiency in technologies relevant to the subfieldPostdocs demonstrate the following preferred job qualifications: - Ability to independently deliver results in a fast-paced environment- Publications at top-tier, peer-reviewed conferences and/or journals- Exceptional verbal and written communication skills- Expert knowledge in modeling and performance, operationalization, and scalability of scientific techniques and establishing decision strategiesRequired application materials:- CV, which lists all peer-reviewed publications and conferences,- Research statement that outlines your research achievements and future research interests, and- A journal article or book chapter that demonstrates your domain expertise.Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, 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 for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Amazon is looking for talented Postdoctoral Scientists to join the Decision Science & Technology team within Amazon RME for a one-year, full-time research position.The host team is developing novel approaches to Anomaly Detection within our Fulfillment Centers. These algorithms are used to detect issues with our equipment before they progress into breakdowns or impact business operations. A variety of data are collected on the equipment, which must be monitored using powerful and scalable solutions.The postdoc is expected to develop novel algorithms based on Machine Learning that captures and diagnoses these anomalies. Experience with transfer learning and deep learning would be valuable to produce adaptable and scalable solutions.Key job responsibilities• Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community.• Publish your innovation in top-tier academic venues and hone your presentation skills.• Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise.• Be comfortable with a fast-paced work with a lot of unknowns and hands-on engagement.• PhD in a relevant field, received within 2 years of starting the program• Proven publication record in Statistics or Machine Learning* Experience with at least one of Anomaly Detection, Transfer Learning, or Deep Learning• Ability to independently deliver results in a fast-paced environment• Publications at top-tier, peer-reviewed conferences and/or journals• Exceptional verbal and written communication skills• Expert knowledge in modeling and performance, operationalization, and scalability of scientific techniques and establishing decision strategiesAmazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, 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 for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.