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Research Area

Economics

Developing sophisticated approaches and systems to deliver the broadest selection of products and services at the lowest prices.

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  • Dean Foster, Sergiu Hart
    2023
    In order to identify expertise, forecasters should not be tested by their calibration score, which can always be made arbitrarily small, but rather by their Brier score. The Brier score is the sum of the calibration score and the refinement score; the latter measures how good the sorting into bins with the same forecast is, and thus attests to “expertise.” This raises the question of whether one can gain
  • AEA 2023, NABE 2023
    2023
    In order to improve prices at Amazon, we created Pricing Labs, a price experimentation platform. Since we do not price discriminate, we must run product-randomized experiments. We discuss how we randomize to prevent spillovers, run different experimental designs (i.e., crossovers) to improve precision, and control for demand trends and differences in treatment groups to get more precise treatment effect
  • We propose a novel architecture for time series models built upon state-space methods. We jointly estimate many, potentially multivariate, distributions defined using state-space models by partially pooling their parameters across the cross-section. These joint distributions define a novel recurrent neural network. By combining state-space methods and neural networks, we leverage the interpretability of
  • Harsh Parikh, Carlos Vajao, Louise Xu, Eric Tchetgen Tchetgen
    2022
    The fundamental challenge of drawing causal inference is that counterfactual outcomes are not fully observed for any unit. Furthermore, in observational studies, treatment assignment is likely to be confounded. Many statistical methods have emerged for causal inference under unconfoundedness conditions given pre-treatment covariates, including: propensity score-based methods, prognostic score-based methods
  • Partha Ghosh, Dominik Zietlow, Michael Black, Larry Davis, Sonny Hu
    GCPR 2022
    2022
    Generation of photo-realistic images, semantic editing and representation learning are only a few of many applications of high- resolution generative models. Recent progress in GANs have established them as an excellent choice for such tasks. However, since they do not provide an inference model, downstream tasks such as classification cannot be easily applied on real images using the GAN latent space.

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US, Virtual
The Amazon Economics Team is hiring Interns in Economics. We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to work with large and complicated data sets. Some knowledge of econometrics, as well as basic familiarity with Stata, R, or Python is necessary. Experience with SQL, UNIX, Sawtooth, and Spark would be a plus. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. You will learn how to build data sets and perform applied econometric analysis at Internet speed collaborating with economists, data scientists and MBAʼs. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. Roughly 85% of interns from previous cohorts have converted to full time economics employment at Amazon. If you are interested, please send your CV to our mailing list at econ-internship@amazon.com.
US, MN, Minneapolis
AWS Central Economics is an interdisciplinary team on the cutting edge of economics, statistical analysis, and machine learning whose mission is to solve problems that have high risk with abnormally high returns. Our team leverages the strengths of our scientists to build solutions for some of the toughest business problems here at Amazon AWS. We are looking for an exceptionally talented, seasoned, and motivated Economist to manage a team of economists and data scientists to drive the science for AWS. Key job responsibilities Manage a team of economists and data scientists to deliver actionable economic analyses to business leaders, provide leadership on the economics and science used in the analyses, and engage with business leaders to identify challenges AWS faces that call for in-depth economic analyses and to ensure the analyses have their intended impact.
US, VA, Arlington
The People eXperience and Technology Central Science Team (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. We are an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. We are looking for economists who are able to work with business partners to hone complex problems into specific, scientific questions, and test those questions to generate insights. The ideal candidate will work with engineers and computer scientists to estimate models and algorithms on large scale data, design pilots and measure their impact, and transform successful prototypes into improved policies and programs at scale. We are looking for creative thinkers who can combine a strong technical economic toolbox with a desire to learn from other disciplines, and who know how to execute and deliver on big ideas as part of an interdisciplinary technical team. Ideal candidates will work closely with business partners to develop science that solves the most important business challenges. They will work in a team setting with individuals from diverse disciplines and backgrounds. They will serve as an ambassador for science and a scientific resource for business teams, so that scientific processes permeate throughout the HR organization to the benefit of Amazonians and Amazon. Ideal candidates will own the data analysis, modeling, and experimentation that is necessary for estimating and validating models. They will work closely with engineering teams to develop scalable data resources to support rapid insights, and take successful models and findings into production as new products and services. They will be customer-centric and will communicate scientific approaches and findings to business leaders, listening to and incorporate their feedback, and delivering successful scientific solutions. Key job responsibilities Use causal inference methods to evaluate the impact of policies on employee outcomes. Examine how external labor market and economic conditions impact Amazon's ability to hire and retain talent. Use scientifically rigorous methods to develop and recommend career paths for employees. A day in the life Work with teammates to apply economic methods to business problems. This might include identifying the appropriate research questions, writing code to implement a DID analysis or estimate a structural model, or writing and presenting a document with findings to business leaders. Our economists also collaborate with partner teams throughout the process, from understanding their challenges, to developing a research agenda that will address those challenges, to help them implement solutions. About the team We are a multidisciplinary team that combines the talents of science and engineering to develop innovative solutions to make Amazon Earth's Best Employer.
US, WA, Seattle
The People eXperience and Technology Central Science Team (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. We are an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. We are looking for economists who are able to apply economic methods to address business problems. The ideal candidate will work with engineers and computer scientists to estimate models and algorithms on large scale data, design pilots and measure their impact, and transform successful prototypes into improved policies and programs at scale. We are looking for creative thinkers who can combine a strong technical economic toolbox with a desire to learn from other disciplines, and who know how to execute and deliver on big ideas as part of an interdisciplinary technical team. Ideal candidates will work in a team setting with individuals from diverse disciplines and backgrounds. They will work with teammates to develop scientific models and conduct the data analysis, modeling, and experimentation that is necessary for estimating and validating models. They will work closely with engineering teams to develop scalable data resources to support rapid insights, and take successful models and findings into production as new products and services. They will be customer-centric and will communicate scientific approaches and findings to business leaders, listening to and incorporate their feedback, and delivering successful scientific solutions. Key job responsibilities Use causal inference methods to evaluate the impact of policies on employee outcomes. Examine how external labor market and economic conditions impact Amazon's ability to hire and retain talent. Use scientifically rigorous methods to develop and recommend career paths for employees. A day in the life Work with teammates to apply economic methods to business problems. This might include identifying the appropriate research questions, writing code to implement a DID analysis or estimate a structural model, or writing and presenting a document with findings to business leaders. Our economists also collaborate with partner teams throughout the process, from understanding their challenges, to developing a research agenda that will address those challenges, to help them implement solutions. About the team We are a multidisciplinary team that combines the talents of science and engineering to develop innovative solutions to make Amazon Earth's Best Employer.
US, WA, Seattle
Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists at Amazon partner closely with senior management, business stakeholders, scientist and engineers, and economist leadership to solve key business problems ranging from Amazon Web Services, Kindle, Prime, inventory planning, international retail, third party merchants, search, pricing, labor and employment planning, effective benefits (health, retirement, etc.) and beyond. Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets – applied macro/time series, applied micro, econometric theory, empirical IO, empirical health, labor, public economics and related fields are all highly valued skillsets at Amazon. You will work in a fast moving environment to solve business problems as a member of either a cross-functional team embedded within a business unit or a central science and economics organization. You will be expected to develop techniques that apply econometrics to large data sets, address quantitative problems, and contribute to the design of automated systems around the company.
US, WA, Seattle
Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists at Amazon partner closely with senior management, business stakeholders, scientist and engineers, and economist leadership to solve key business problems ranging from Amazon Web Services, Kindle, Prime, inventory planning, international retail, third party merchants, search, pricing, labor and employment planning, effective benefits (health, retirement, etc.) and beyond. Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets – applied macro/time series, applied micro, econometric theory, empirical IO, empirical health, labor, public economics and related fields are all highly valued skillsets at Amazon. You will work in a fast moving environment to solve business problems as a member of either a cross-functional team embedded within a business unit or a central science and economics organization. You will be expected to develop techniques that apply econometrics to large data sets, address quantitative problems, and contribute to the design of automated systems around the company.
US, WA, Seattle
Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists at Amazon partner closely with senior management, business stakeholders, scientist and engineers, and economist leadership to solve key business problems ranging from Amazon Web Services, Kindle, Prime, inventory planning, international retail, third party merchants, search, pricing, labor and employment planning, effective benefits (health, retirement, etc.) and beyond. Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets – applied macro/time series, applied micro, econometric theory, empirical IO, empirical health, labor, public economics and related fields are all highly valued skillsets at Amazon. You will work in a fast moving environment to solve business problems as a member of either a cross-functional team embedded within a business unit or a central science and economics organization. You will be expected to develop techniques that apply econometrics to large data sets, address quantitative problems, and contribute to the design of automated systems around the company.
US, CA, San Francisco
Job summary MULTIPLE POSITIONS AVAILABLE Company: AMAZON.COM SERVICES LLC Position Title: Economist II Location: San Francisco, California Position Responsibilities: Work with fellow economists, scientists and/or senior management on key business problems faced in retail, international retail, third party merchants, search, and/or operations. Apply the frontier of economic thinking to experiment design, forecasting, program evaluation and other areas. Build econometric models using data systems. Apply economic theory to solve business problems. Own the development of economic models and manage the data analysis, modeling and experimentation necessary to estimate and validate the models, in collaboration with scientists and engineers. Develop new techniques to process large data sets, address quantitative problems, and contribute to design of automated systems. Apply tools from applied micro-econometrics (e.g. experimental design, difference-in-difference, regression discontinuity) and forecasting (essential time series models). Leverage big data tools for data extraction. Work closely with business partners to communicate the intuition, implication and detail of economic analyses/modeling and incorporate feedback. Write up and present analysis for distribution to various levels of management at Amazon. Amazon.com is an Equal Opportunity-Affirmative Action Employer - Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.#0000
US, WA, Seattle
The Amazon Economics Team is hiring Interns in Economics. We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to work with large and complicated data sets. Some knowledge of econometrics, as well as basic familiarity with Stata, R, or Python is necessary. Experience with SQL, UNIX, Sawtooth, and Spark would be a plus. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. You will learn how to build data sets and perform applied econometric analysis at Internet speed collaborating with economists, data scientists and MBAʼs. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. Roughly 85% of interns from previous cohorts have converted to full time economics employment at Amazon. If you are interested, please send your CV to our mailing list at econ-internship@amazon.com.
US, WA, Seattle
Job summary We are looking for a leader of Science on the Seller Fees team. In this role, you will lead a team of economists and machine learning (ML) scientists to develop our fee pricing models worldwide. You will own the development of causal models to help isolate the impact of fee and policy changes from other business actions, using experiments where possible, or observational data when it is not. You will leverage ML techniques to estimate seller economics at scale. You will guide the development of optimization models to balance the long term growth and profitability of Amazon stores. The ideal candidate will have strong technical knowledge across Economics and ML, a proven ability to lead a team scientists, and will be an effective communicator with senior leadership. They will enjoy working on ambiguous problems and will have strong business acumen. They will serve as a key member of the Seller Fees leadership team with peers that include Fee Strategy, Software Engineering, Fee Seller Experience, and Fee Integrity. Key job responsibilities • Lead a team of ~25 people across technical job families (Applied Scientists, Data Scientists, Economists, Data Engineers…) • Shape the thinking of the monetization of the Amazon marketplace with senior leaders across Amazon • Manage a research agenda that balances short term deliverables with measurable business impact with long term, high risk / high reward projects • Own a portfolio of science-based products (e.g. simulation platforms) to support stakeholders worldwide • Provide technical and scientific guidance to team members. • Partner with academics to advance research in causal modeling • Hire and develop top talent • Collaborate with business and software teams both within and outside of fees for prioritization and resources A day in the life Typical activities include: Brainstorm new causal modeling approach with senior scientists Host a Fee Science MBR Review fee impact analysis with EU business team Connect with tech team on product roadmap priorities Plan a fun holiday team get together with EA About the team The Seller Fees team owns the end-to-end fees experience for two million active third party sellers who sell their products in our stores. We own the fee strategy, fee seller experience, fee accuracy and integrity, fee science and analytics, and we provide scalable technology to monetize all services available to third-party sellers.