Join our Private Brand Intelligence (PBI) organization in building AI driven solutions at scale to delight our customers with products across our leading private brands such as Amazon Basics, Amazon Essentials, and by Amazon.

PBI applies Generative AI, Machine Learning, Statistics, and Economics to derive actionable insights about the complex economy of Amazon’s retail business. We also develop ML/Econ models and algorithms to drive strategic business decisions and improve operations. We are an interdisciplinary team, using SOTA science and technology and leveraging the strengths of engineers, economists and scientists to build solutions for some of the toughest business problems at Amazon, covering areas such as pricing, promotion, discovery, customer love, supply chain and product selection/development.

We are looking for an Economist who is strong in applying SOTA econometrics and machine learning methodologies to conduct empirical research and implement science solutions that solve real-world business problems. The candidate will not only implement and validate models on large scale data, and but also help business and tech partners understand the results and turn them into policies, programs, and actions that have a major impact on Amazon’s business. We are looking for creative thinkers who can combine a strong economic toolbox with a desire to learn from others, and who know how to execute and deliver on big ideas.

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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Key job responsibilities
• You own and solve difficult problems, delivering economic models and artifacts that successfully support business decisions.
• You work directly with business partners. You are able to translate their questions into technical frameworks (e.g., designing a test to estimate a causal effect for a binary treatment).
• You are well-versed in the pros and cons of at least one economic modelling framework and how it is best applied. You have some working experience with the applications of other frameworks. For example, you may have strong expertise in RDD, with experience in matching estimators and ML-causal models.
• You are able to gather and use difficult data sets across domains. You proactively gather data when it is not readily available.
• Your work is consistently of high quality (e.g., accurate, well-communicated, efficient). Your solutions do not require refinement to deliver value. You are able to justify your approach.
• You deliver projects within expected timeframes. You are able to plan your own work to balance the business need for timely technical inputs with the need for scientific rigor and careful use of the data.
• You write clear and factually correct technical documents. You are able to explain economic and econometric concepts to non-economist scientists.
• You provide meticulous, constructive reviews for economist peers (models, code, and other artifacts).
• You recognize discordant views and take part in constructive dialogue to resolve them.
• You are able to confidently train new team-mates about your customers, how your economic solutions work, and how those solutions are reflected in the data.
• You recognize when a problem requires methods from a different sub-field and seek out appropriate guidance.