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  • The impact of sustainability programs on consumer purchase behavior: Evidence from Amazon
    Davide Proserpio, Ali Goli, Tyler Mangini, Ken Lau, Daniela Yu
    International Journal of Research in Marketing
    2025
    In 2020, Amazon launched the Climate Pledge Friendly (CPF) program to make it easy for customers to discover and shop for products with sustainability certifications. In this paper, we measure the causal impact of products qualifying for CPF on consumer purchase behavior. Using a dataset of about 45,000 products spanning three categories, and a Differencein-Differences identification strategy, we show that
    Economics
  • CLOUD-CG: Clustering on longitudinal causal graphs
    Nakamura Sakai Shinpei, Yuhe Gao, Chi-Hui Yen, Christoph Scheidiger, Jasjeet Sekhon
    AAAI 2025 Workshop on AI for Social Impact
    2025
    To the best of our knowledge, this work introduces the first framework for clustering longitudinal data by leveraging time-dependent causal representation learning. Clustering longitudinal data has gained significant attention across various fields, yet traditional methods often overlook the causal structures underlying observed patterns. Understanding how covariates influence outcomes is critical for policymakers
    Economics
  • Adaptive experimentation when you can’t experiment
    Yao Zhao, Kwang-Sung Jun, Tanner Fiez, Lalit Jain
    2023 Conference on Digital Experimentation @ MIT (CODE@MIT), NeurIPS 2024
    2024
    This paper introduces the confounded pure exploration transductive linear bandit (CPET-LB) problem. As a motivating example, often online services cannot directly assign users to specific control or treatment experiences either for business or practical reasons. In these settings, naively comparing treatment and control groups that may result from self-selection can lead to biased estimates of underlying
    Economics
  • Performance of synthetic diff-in-diff models for geo-randomized experiments
    Paula Meloni, Stefan Hut, Mahnaz Islam
    2024 Conference on Digital Experimentation @ MIT (CODE@MIT)
    2024
    There are different reasons why experimenters may want to randomize their experiment at a region level. In some cases, treatments cannot be turned on or off at the individual level, therefore requiring randomization at a group level, for which regions can be a good candidate. In other cases, experimenters may worry about network effects or other types of spillovers within a geographic area, and opt to randomize
    Economics
  • Scalable heterogeneity detection in online experiments
    Hammaad Adam, Merlin Heidemanns, Doug Hains, James McQueen
    2024 Conference on Digital Experimentation @ MIT (CODE@MIT)
    2024
    Online sites typically evaluate the impact of new product features on customer behavior using online controlled experiments (or A/B tests). For many business applications, it is important to detect heterogeneity in these experiments [1], as new features often have a differential impact by customer segment, product group, and other variables. Understanding heterogeneity can provide key insights into causal
    Economics
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Intern - Economics, WW Returns & ReComm Tech& Inn
US, WA, Bellevue
Amazon is committed to exceeding customer expectations. In the Returns and Recommerce organization, we seek to improve customer satisfaction with the items they buy on Amazon, provide new value for our customers, and reduce costs to drive the holistic business flywheel. The Return and Recommerce team is looking for an Economist intern with time series forecasting skills to join our cross-domain group of economists, applied scientists, and business intelligence engineers. We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to work with large and complicated data sets, and train and deploy time series forecasting solutions at scale. Knowledge of time-series forecasting as well as basic familiarity with either Python or R is necessary. Experience in Bayesian modelling or geospatial forecasting 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 collaborating with economists, scientists, and product managers. 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 previous cohorts have converted to full time economist employment at Amazon. If you are interested, please send your CV to our mailing list at econ-internship@amazon.com.
Economist, International Seller Service
US, VA, Arlington
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. About the team The International Seller Services (ISS) Economics team is a dynamic group at the forefront of shaping Amazon's global seller ecosystem. As part of ISS, we drive innovation and growth through sophisticated economic analysis and data-driven insights. Our mission is critical: we're transforming how Amazon empowers millions of international sellers to succeed in the digital marketplace. Our team stands at the intersection of innovative technology and practical business solutions. We're leading Amazon's transformation in seller services through work with Large Language Models (LLMs) and generative AI, while tackling fundamental questions about seller growth, marketplace dynamics, and operational efficiency. What sets us apart is our unique blend of rigorous economic methodology and practical business impact. We're not just analyzing data – we're building the frameworks and measurement systems that will define the future of Amazon's seller services. Whether we're optimizing the seller journey, evaluating new technologies, or designing innovative service models, our team transforms complex economic challenges into actionable insights that drive real-world results. Join us in shaping how millions of businesses worldwide succeed on Amazon's marketplace, while working on problems that combine economic theory, advanced analytics, and innovative technology.
Intern - Economics, Amazon Health Services
US, WA, Seattle
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 Python is necessary, and experience with SQL and UNIX would be a plus. This position is focused on forecasting and financial modeling. 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, scientists, and product managers. 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 previous cohorts have converted to full time economist employment at Amazon. If you are interested, please send your CV to our mailing list at: econ-internship@amazon.com.
Economist Manager, CBA
US, WA, Seattle
Amazon.com is seeking a Manager to lead a science team within Customer Forecasting and Valuation (CFV). We own a set of primary decision metrics at Amazon, leveraging causal machine-learning models to predict the long-term impact of customer actions. These metrics drive several investment and launch decisions across Amazon. This fast-paced, cross-disciplinary team of economists and scientists leverages advanced machine learning, statistics, and economics to solve complex problems like measuring the long-term causal effects of Amazon initiatives. CFV is part of the Customer Behavior Analytics (CBA) organization, which is responsible for developing the architecture, design, and implementation of tools used to understand customer behavior and value generation across the company's Retail business. As a manager within CFV, you will lead and collaborate with Applied Scientists, Economists, and Data Scientists to work backwards from customer needs and translate product ideas into concrete deliverables. This will involve inventing scalable causal measurement solutions that provide highly accurate and actionable insights, and drive improvement in key customer lifetime value metrics. You will interface directly with product owners, senior scientists/economists, and business leadership to create multi-year research and product agendas that drive step-change growth. Working with massive datasets spanning billions of customer transactions, you will partner closely with a dedicated engineering team to uncover insights that propel Amazon's Retail business forward. The role will also be an important collaborator with other science teams at CBA and Stores. The ideal candidate will have experience with machine learning models, causal inference, and a strong background in applied science, economics, and engineering. You should also possess creativity, curiosity, and excellent judgment to thrive in an environment of ambiguity. If you are seeking an opportunity to drive innovation, solve real-world problems using advanced analytics, and grow your career over time, this role on Amazon's industry-leading CBA team may be the perfect fit.
Intern - Economics, WW Returns & ReCommerce
US, WA, Bellevue
The Returns Economics Intelligence team brings together economists, data scientists, data analysts, and business intelligence engineers to deliver innovative research and products that discover and surface returns-influencing behavior, trends and their root causes. We leverage a range of scientific approaches such as causal modeling, structural and choice modeling, time series, ML, and optimization models to yield tangible insights targeted at reducing the cost of returns and concessions without slowing down the Amazon flywheel. We are looking for a detail-oriented, organized and responsible Economist intern with strong skills in time series and macroeconomic modeling. We are a new team at Amazon and this is a great opportunity to be on the leading edge. Roughly 85% of interns from previous cohorts have converted to full time economist employment at Amazon. If you are interested, please apply and send your CV to our mailing list at econ-internship@amazon.com.
Economist II, AWS Central Economics and Science
US, WA, Seattle
We are hiring an Economist to work on understanding and accelerating AWS customer growth. This will involve generating insights on customer growth on AWS, deriving specific policy recommendations to accelerate growth, and planning and executing experiments and/or rigorous quasi-experimental analyses to test out these recommendations. Key job responsibilities This role with interface with product owners, scientists/economists, and leadership to create and execute research agendas that drive step change growth for the business. The role will also be an important collaborator with other science teams at AWS. A day in the life Our team takes big swings and works on hard cross organizational problems where the optimal success rate is not 100%. We also ask people to grow their skills and stretch and make sure we do it in a supportive and fun environment. It’s about empirically measured impact, advancement, and fun on our team. We work hard during work hours but we also don’t encourage working at nights or on weekends except in very rare, high stakes cases. Burn out isn’t a successful long run strategy. Because we invest in the long run success of our group it’s important to have hobbies, relax and then come to work refreshed, and excited. It makes for bigger impact and faster skill accrual and thus career advancement. About the team Our group is technically rigorous and encourages ongoing academic conference participation and publication. Our leaders are here for you and to enable you to be successful. We believe in being servant leaders focused on influence: good data work has little value if it doesn’t translate into actionable insights that are rolled out and impact the real economy. We are communication centric since being able to explain what we do ensures high success rates and lowers administrative churn. Also: we laugh a lot. If it’s not fun, what’s the point?
Economist Manager, AWS Central Economics and Science
US, NY, New York
We are hiring a manager for a cross-functional team that builds ML-based products to help AWS sellers understand customers and optimize sales strategies. This manager will be an important member of the AWS Central Economics and Science team and help set the science and product direction for their team and, by extension, a large part of the org due to within-org collaboration. Specifically, we’re looking for someone to help define a growth- and business-focused vision for the team. An ideal candidate will think big and understands how to use science to drive measurable incremental business impact by taking insights all the way through to actions that manifest in the real economy. This will be a great opportunity to utilize both causal/econ and ML chops. Someone who has worked on embedded teams or on central science teams with policy implementation involvement is ideal. This role lends itself to increased scope and career growth over time. Key job responsibilities This role with interface directly with product owners, scientists/economists, and leadership to create multi-year research and product agendas that drive step change growth for the business. The role will also be an important collaborator with other science teams at AWS. A day in the life Our team takes big swings and works on hard cross organizational problems where the optimal success rate is not 100%. We also ask people to grow their skills and stretch and make sure we do it in a supportive and fun environment. It’s about empirically measured impact, advancement, and fun on our team. We work hard during work hours but we also don’t encourage working at nights or on weekends except in very rare, high stakes cases. Burn out isn’t a successful long run strategy. Because we invest in the long run success of our group it’s important to have hobbies, relax and then come to work refreshed and excited. It makes for bigger impact, faster skill accrual and thus career advancement. About the team Our group is technically rigorous and encourages ongoing academic conference participation and publication. Our leaders are here for you and to enable you to be successful. We believe in being servant leaders focused on influence: good data work has little value if it doesn’t translate into actionable insights that are rolled out and impact the real economy. We are communication centric since being able to explain what we do ensures high success rates and lowers administrative churn. Also: we laugh a lot. If it’s not fun, what’s the point?
Economist III, AWS Central Economics and Science
US, WA, Seattle
We are hiring a Senior Economist with the ability to disambiguate very challenging structural problems in two and multi-sided markets. The right hire will be able to dive deep into the data to come up with stylized facts, build reduced form models that motivate structural assumptions, and build to more complex structural models. The main use case will be understanding how the incremental effects of subsidies to a two sided market relate to sales motions characterized by principal agent problems. Key job responsibilities This role with interface directly with product owners, scientists/economists, and leadership to create multi-year research agendas that drive step change growth for the business. This role is important for the development of the strategic direction of the AWS Central Economics and Science team. The role will also be an important collaborator with other science teams at AWS. A day in the life Our team takes big swings and works on hard cross organizational problems where the optimal success rate is not 100%. We also ask people to grow their skills and stretch and make sure we do it in a supportive and fun environment. It’s about empirically measured impact, advancement, and fun on our team. We work hard during work hours but we also don’t encourage working at nights or on weekends except in very rare, high stakes cases. Burn out isn’t a successful long run strategy. Because we invest in the long run success of our group it’s important to have hobbies, relax and then come to work refreshed, and excited. It makes for bigger impact and faster skill accrual and thus career advancement. About the team Our group is technically rigorous and encourages ongoing academic conference participation and publication. Our leaders are here for you and to enable you to be successful. We believe in being servant leaders focused on influence: good data work has little value if it doesn’t translate into actionable insights that are rolled out and impact the real economy. We are communication centric since being able to explain what we do ensures high success rates and lowers administrative churn. Also: we laugh a lot. If it’s not fun, what’s the point?
Principal Economist, PXT Central Science
US, VA, Arlington
The Central Science Team within Amazon’s People Experience and Technology org (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. We are an interdisciplinary team, which combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. We are looking for a Principal Economist who is able to provide structure around complex business problems, hone those complex problems into specific, scientific questions, and test those questions to generate insights. The ideal candidate will work with various science, engineering, operations, and analytics teams 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. They will lead research projects to produce robust, objective research results and insights which can be communicated to a broad audience inside and outside of Amazon. Ideal candidates will work closely with business partners to develop science that solves the most important business challenges. They will work well 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 development of scientific models and manage the data analysis, modeling, and experimentation that is necessary for estimating and validating models. They will be customer-centric – clearly communicating scientific approaches and findings to business leaders, listening to and incorporate their feedback, and delivering successful scientific solutions. About the team The Central Science Team within Amazon’s People Experience and Technology org (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. We are an interdisciplinary team, which combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal.
Senior Economist, Tech Lead, Amazon
US, WA, Seattle
Amazon's Global XCM organization (Cross-Category, Cross-Channel Marketing) is looking for a talented Tech Lead Senior Economist who is interested in solving one of the most challenging business problems in marketing measurement and optimization, and developing cutting-edge ML model. Working with our team of data scientists, applied scientists, research scientists, and economists, this leader will help redefine scalable marketing measurement and optimization. XCM’s mission is to be the most culturally and contextually aware, creatively breakthrough, and measurably effective marketing organization in the world. In this role, you will be a technical leader in Econometric research with significant scope, impact, and high visibility. You will lead strategic measurement and optimization science initiatives in collaboration with external science teams, and development and deployment of measurement and real-time predictive and optimization science models. As a successful Economist, you are an analytical problem solver who enjoys diving into data, leads problem solving, guides development of new frameworks, writes code, is excited about investigations and algorithms, and can credibly interface between technical teams and business stakeholders. You are an expert in causal inference models to solve business problems. You are a hands-on innovator who can contribute to advancing Marketing measurement technology and push the limits on what’s scientifically possible with a razor sharp focus on measurable customer and business impact. You will also coach and guide junior scientists in the team to grow the team’s talent and scale the impact of your work. Key job responsibilities - Design and implement production-ready causal machine learning models to solve complex measurement and optimization challenges - Partner with cross-functional science teams to drive innovative high-impact initiatives - Collaborate with key stakeholders to develop strategic roadmaps and ensure successful project execution - Mentor junior scientists and establish technical best practices for the team
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