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  • Proximal causal inference for synthetic control with surrogates
    Jizhou Liu, Eric J. Tchetgen Tchetgen, Carlos Varjao
    AISTATS 2024
    2024
    The synthetic control method (SCM) has become a popular tool for estimating causal effects in policy evaluation, where a single treated unit is observed. However, SCM faces challenges in accurately predicting postintervention potential outcomes had, contrary to fact, the treatment been withheld, when the pre-intervention period is short or the post-intervention period is long. To address these issues, we
    Economics
  • Nowcasting recession risk
    Francesco Furno, Domenico Giannone
    IAAE 2023, Research Methods and Applications on Macroeconomic Forecasting
    2024
    We propose a simple yet robust framework to nowcast recession risk at a monthly frequency in both the United States and the Euro Area. Our nowcast leverages both macroeconomic and financial conditions, and is available the first business day after the reference month closes. In particular, we argue that financial conditions are not only useful to predict future downturns–as emphasized by the existing literature–but
    Economics
  • Efficient switchback experiments via multiple randomization designs
    Lorenzo Masoero, Guido Imbens, Thomas Richardson, James McQueen, Suhas Vijaykumar, Ido Rosen
    2023 Conference on Digital Experimentation @ MIT (CODE@MIT)
    2023
    Online A/B tests have become an indispensable tool across all the technology industry: if performed correctly, “online” experiments can inform effective decision making and product development. It should therefore not be surprising that Gupta et al. [2019] estimates that online businesses alone collectively run hundreds of thousands of experiments annually. Modern online experiments are often run in marketplaces
    Economics
  • Cross-unit spillovers in A/B testing: Empirical evidence from ads
    Ronak Jain, Stefan Hut, Mahnaz Islam, Yao Pan
    2023 Conference on Digital Experimentation @ MIT (CODE@MIT)
    2023
    Randomized Control Trials (RCTs) are widely used across Amazon to causally estimate impacts of proposed feature changes, in order to make data-driven launch decisions. A key element of experimental design is the level of randomization, and the choice often relies on the cross-unit interaction structure. For instance, in the context of advertiser experiments, a treatment may affect the outcome of control
    Economics
  • Value of stratification in cluster-randomized experiments
    Stefan Hut, Blake Mason, Mahnaz Islam, Lledo Esquerra
    2023 Conference on Digital Experimentation @ MIT (CODE@MIT)
    2023
    There are many experimental settings that may suffer from cross-unit (customers, seller, advertiser, etc.) spillovers, for instance through network effects. Such effects introduce bias and prevent the experimenter from drawing trustworthy insights on the data. One approach to dealing with such spillovers is to group units into clusters and randomize treatment status at the cluster level. Examples of clusters
    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, 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 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.
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
Sr. Economist, Seller Economics-Fixed, Seller Economics
US, WA, Seattle
The Selling Partner Fees team owns the end-to-end fees experience for two million active 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. This person will work on the development of economic, statistical and machine learning models to understand third party seller behaviors and enhance our fee optimization models. The ideal candidate needs to be comfortable transitioning between theoretical Economic models and empirical ones, and use the combination of these models to provide guidance for fee setting. A successful Economist in this role 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 theoretical and empirical models to assess the causal impact of fees on third party sellers’ behavior and business performance. - Lead enhancements into existing fee calculation models to maximize the long term health of the Amazon third-party marketplace. - 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.
Sr. Economist, Seller Economics-Fixed
US, WA, Seattle
The Selling Partner Fees team owns the end-to-end fees experience for two million active 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. 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. Responsibilities: · Design and develop rigorous models to assess the causal impact of fees on third party sellers’ behavior and business performance. · Lead enhancements into existing fee calculation models to maximize the long term health of the Amazon third-party marketplace. · Own the scientific vision and direction related to fees 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.
Senior Economist, Program Valuation, Fashion Intelligence
US, WA, Seattle
At Amazon, we're committed to pioneering new frontiers in customer experience, and Fashion Tech is at the forefront of this mission. Our programs and technologies are revolutionizing how customers interact with fashion products, presenting unique challenges and opportunities for quantifying their economic impact. We're seeking a highly experienced Economist with expertise in causal modeling to lead our efforts in understanding the economic impact of our efforts in this dynamic space. Over the years, teams across Amazon have built systems that can value content and even optimize what is shown based on relevant ‘value’ metrics. However, understanding attribution and program incrementality continue to be challenges that require tying the business context with the most relevant methodology from an array of possible ones. The person in this role will work with finance, CBA and business owners to define the right metrics and methodologies to compute attributed and incremental value of programs and features, while leveraging existing frameworks wherever applicable. We want to answer questions like “If this program didn’t exist, what is the total economic value to Amazon that we would stand to lose?” and “What is the ongoing business impact of this CX post-launch?”. Key job responsibilities - Spearhead collaborative efforts with finance, CBA (Cost-Benefit Analysis), and business teams to define robust metrics and methodologies for measuring the attributed and incremental value of Fashion Tech programs and features. - Develop advanced frameworks and models to assess the causal economic impact of content, programs, and customer experience enhancements throughout the customer purchase funnel. - Lead the resolution of complex challenges related to content attribution and program incrementality, leveraging existing systems and methodologies while exploring innovative approaches where necessary. - Conduct in-depth economic analyses to address critical business questions, such as estimating the economic value of key programs and evaluating the ongoing business impact of post-launch customer experience improvements. - Drive cross-functional collaboration with data scientists, economists, and business leaders to integrate economic insights into strategic decision-making processes and shape future initiatives. - Stay at the forefront of industry trends, economic research, and best practices in causal modeling and econometric techniques, continuously enhancing our methodologies and frameworks to ensure relevance and effectiveness. About the team The Fashion Tech organization has a mission to make Amazon the most-loved fashion destination globally through technology by building novel experiences that bring a diverse breadth of customers to shop fashion in the Amazon store. The Fashion Intelligence team improves the speed, accuracy, and standards of data driven decisions across all programs within Fashion Tech. As a central analytics team, our goal is to break silos and identify interconnectedness across Fashion Tech programs, keeping the customer at the center. Here at Fashion & Fitness, we are inspired to never stop embracing our uniqueness for both our employees and our customers.
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