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  • CLOUD-CG: Clustering on longitudinal causal graphs
    Shinpei Nakamura-Sakai, 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
  • Overcoming the winner’s curse: Leveraging Bayesian inference to improve estimates of the impact of features launched via A/B tests
    Ryan Kessler
    2024 Conference on Digital Experimentation @ MIT (CODE@MIT)
    2024
    Many data-driven companies measure the impact of product groups and allocate resources across them based 2 on the estimated impacts of features they launch via A/B tests. In this doc, we show that, when based on a standard 3 frequentist estimator of the impact of features, this practice can significantly overstate the impact of product groups and 4 distort the allocation of resources. When this practice
    Economics
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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. 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.
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.
Economist, Ads Econ
US, WA, Seattle
The Advertising Economics team is looking for a PhD economist to lead high-impact science projects using state of the art econometrics and ML to maximize the impact of our Ad Sales investments. In this role, you will deliver on mission critical goals that affects the high-level strategy of our ads business. Therefore, the ability to communicate effectively with both technical and non-technical audiences is essential to the candidate’s success. On the methodological front, we are particularly interested in candidates with a strong causal inference background but who also bring complementary skills such as empirical IO, machine learning, or experience working with unstructured audio/text data. Advertising is used daily to surface new selection and provide customers a wider set of product choices along their shopping journeys. The business is focused on generating value for shoppers as well as advertisers. Our team uses a combination of econometrics, machine learning, and data science to build disruptive products for our Advertising stakeholders. We also generate insights to guide Amazon Advertising strategy, providing direct support to senior leadership. https://w.amazon.com/bin/view/GMACEconomics/AdsCoreEcon/AdSales/ Key job responsibilities Leverage econometrics and ML models to optimize advertising strategies on behalf of our customers. Influence key business and product decisions based on insights from models you develop. Identify and pitch new opportunities to leadership that are suggested by the data. Partner with other science leaders throughout Amazon to develop consistent and repeatable solutions. Design, execute, and analyze experiments (A/B testing etc.) to evaluate different strategies. Work with other scientists, software developers, and product partners to implement your solutions.
Economist II, Marketing Measurements, CMO Science
US, WA, Seattle
The Campaign Measurement & Optimization (CMO) organization is looking for a experienced Economist interested in solving one of the most challenging business problems in marketing measurement and developing innovative structural causal models. Working with our team of data scientists, applied scientists, and economists, this economist will help redefine scalable marketing measurement at Amazon and its subsidiaries. The Campaign Measurement & Optimization (CMO) organization’s mission is to be the most trusted source of measurement science solutions to drive marketing investment decisions across Amazon. The CMO team provides incrementality and efficiency measurement services to the marketing stakeholders across Amazon’s Stores suit of businesses. CMO applies industry leading causal inference models to measure omni-channel effectiveness of marketing campaigns from these businesses worldwide. Our outputs shape Amazon product and marketing teams’ decisions and therefore how Amazon customers see, use, and value their experience with Amazon. This is a high-impact role with opportunities to develop systems and analyze marketing effectiveness that contributes billions of dollars to the business. As an Economist, you will be responsible for the design and development of the state-of-the-art measurement and optimization models, while collaborating with other scientists, businesses, marketers, and software teams to solve key challenges facing the teams. Such challenges include measuring the incremental impact of multi-channel marketing portfolios, estimating the impact on long term inter-related customer actions, and scaling measurement solutions for WW marketplaces. Unlike many companies who buy existing off-the-shelf marketing measurement systems, we are responsible for studying, designing, and building systems to serve Amazon’s suite of businesses. Our team members have an opportunity to be on the forefront of marketing measurement thought leadership by working on some of the most difficult problems in the industry with some of the best product managers, scientists, economists and software developers in the business. Key job responsibilities In this role, you will be a technical leader in Econometric research with significant scope, impact, and high visibility. You will own developing the next generation of Marketing-Mix-Media (MMM) models combining structural and reduced form econometric techniques. Your solution will deliver to business leaders accurate and actionable incrementality estimates to improve their marketing portfolio optimization. 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 proficient in structural models to solve business problems. You are a hands-on innovator who can contribute to advancing Marketing measurement technology in a B2C and B2B environment, 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.
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.
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.
Sr. Economist, Seller Economics, Seller Fee Science
US, WA, Seattle
The Selling Partner Fees team owns the end-to-end fees experience for third party sellers. 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. We are looking for a Senior Economist to lead the development of economic models and tools to optimize the structure and magnitude of fees paid by >4MM of heterogeneous Sellers Worldwide, and to design incentives and experiments to make sure our customers see the best selection. The ideal candidate will be an influencer with technical skills and a practical mindset. They will lead the development of economic, statistical and machine learning models to understand third party seller behaviors and enhance our fee optimization models. This candidate will be comfortable leading research in unexplored areas and communicating their findings with senior leadership. They will enjoy dealing with ambiguous problems and working in a fast-paced and dynamic environment. The position also requires collaboration with other scientists (Economists, Data Scientists…), Strategy Analysts, Product Managers and Software Developers. Key job responsibilities Design and develop rigorous models and experiments to assess the causal impact of fees on third party sellers’ behavior and business performance. · Lead enhancements into existing fee models to maximize the long term health of the Amazon third-party marketplace. · Own scientific direction of key fee questions worldwide. · Collaborate with product managers, data scientists, and software developers to incorporate models into production processes and influence senior leaders. · Act as ambassador of the fees scientific community.
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?
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