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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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  • 2023 Conference on Digital Experimentation @ MIT (CODE@MIT)
    2023
    Network interference, where observed outcomes are influenced by interaction with nearby units, is a fundamental issue in A/B testing and experimentation in social and economic networks. Clustered randomization is a frequently-used strategy that aims to prevent confounding by limiting interaction between treated and untreated units. We study a model of least-squares estimation under network interference,
  • Chen Chen, Jonathan Rothwell, Pedrito Maynard-Zhang
    AERA 2023 Workshop on Multimodal Literacy in OST Programs: Family and Community Ties
    2023
    Computer science (CS) is special among STEM subjects: it aims at an industry sector that has the most job growth but has a constant shortage in the workforce; it is a relatively young and burgeoning subject in K-12 education that has a shortage of classroom teachers; and it is one of a very few STEM subjects that large number of students can master by learning it completely out-of-school. To inspire the
  • Statistical Science
    2023
    Classical Randomized Controlled Trials (RCTs), or A/B tests, are designed to draw causal inferences about a population of units, for example, individuals, plots of land or visits to a website. A key assumption underlying a standard RCT is the absence of interactions between units, or the stable unit treatment value assumption (Ann. Statist. 6 (1978) 34-58). Modem experimentation, however, is often conducted
  • Dean Foster, Sergiu Hart
    Theoretical Economics
    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
  • Joe Cooprider, Shima Nassiri
    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

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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. 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.
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.
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
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.
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.
US, WA, Seattle
Amazon is seeking an innovative and talented Economist to join our Stores Ads Science team. In this role, you will play a crucial role in developing and implementing advanced econometrics and machine-learning solutions to solve complex business problems in a highly ambiguous problem space at the intersection of Amazon’s Stores and Advertising businesses, and deliver measurable business impacts via cross-team and cross-functional collaboration. This position requires a blend of technical expertise, leadership skills, and the ability to drive projects from conception to production. Amazon is investing heavily in building a world-class advertising business. Our advertising products are strategically important to Amazon’s Retail and Marketplace businesses for driving long-term growth. The Stores Ads Science team is dedicated to identifying and capitalizing on opportunities that jointly optimize Amazon's Stores and Advertising businesses. We focus on leveraging advertising signals to enhance Stores' decision-making processes and vice versa, ultimately driving long-term economic value for shoppers, sellers/vendors, and Amazon. We collaborate closely with tech and product teams across Stores and Advertising, continuously advancing experimentation methodologies to accelerate scientific development and quantify business impacts. Our team is characterized by high motivation, strong collaboration, and an entrepreneurial spirit with a bias for action. Key job responsibilities - Develop economic theory and deliver econometrics and machine learning models at scale. - Design, conduct, and analyze complex experiments to validate hypotheses and quantify the impact of new algorithms and features - Collaborate with cross-functional teams to translate research into scalable, production-ready solutions - Drive data-driven decision making to optimize Amazon's Stores and Advertising ecosystem - Write effective business narratives and scientific papers to communicate to both business and technical audiences
US, WA, Seattle
The Worldwide Defect Elimination (WWDE) Team within Amazon Customer Service is seeking a highly skilled economist to estimate the customer impact of each Customer Service action. Your analysis will assist teams across Amazon to prioritize defect elimination efforts and optimize how we respond to customer contacts. You will partner closely with our product, program, and engineering teams to deliver your findings to users via systems and dashboards that guide Customer Service planning and policies. Key job responsibilities - Develop causal, economic, and machine learning models at scale. - Engage in economic analysis; raise the bar for research. - Inform strategic discussions with senior leaders across the company to guide policies. A day in the life If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: * Medical, Dental, and Vision Coverage * Maternity and Parental Leave Options * Paid Time Off (PTO) * 401(k) Plan About the team The WWDE team's mission is to understand and resolve all issues impacting customers and connect all organizations in Amazon to customer experiences. Our vision is to be the ultimate steward of the Voice of the Customer (VoC), empowering CS and Amazon teams to easily measure, listen, and act on customer feedback. The team broadly supports defect detection, root cause identification, and resolution to earn customer trust. The Customer Service Economics & Optimization team is a force multiplier within this group. Through causal analysis, we estimate the effectiveness of our efforts to delight the customer.
US, WA, Seattle
Join us at Amazon as we reinvent shopping again! We're not just talking about improving the existing Amazon shopping experiences, we're building a brand-new world where shopping is effortless and intuitive through the power of generative AI. Leveraging state-of-the-art Large Language Models and generative AI, we're creating a live, two-way natural language conversational experience that is fast, helpful and trustworthy. As people turn to Amazon for deeper insights and understanding about products earlier and earlier in their shopping journeys, we're stepping up to the challenge by synthesizing complex information and multiple perspectives so customers can explore Amazon’s vast catalog to find exactly the products that solve their particular needs. Imagine having a back and forth conversation with an AI assistant helping you to articulate a problem you’re trying solve, effortlessly answering your product questions and giving you trustworthy advice and recommendations for what to buy. Also imagine a world where this same AI assistant reduces your mental load by proactively predicting and then fulfilling your shopping needs without you needing to interfere, thus saving you time and money along the way. We are building such an AI assistant to become the digital manifestation of the helpful salesperson that asks customers what they need, helps them navigate the store, waits unobtrusively while they look over the shelves, and helps them find complementary goods. What does economics have to teach this salesperson? Can we embed lessons from the behavioral literature to help customers? This is an opportunity to embed economic expertise into large scale generative models. This is just the beginning, and the future is yours to shape. We're searching for pioneers who are passionate about using technology and innovation to fundamentally change how customers shop, and who are ready to make a lasting impact on the industry and even disrupting how Amazon serves customers. You'll be a senior technical leader working with talented scientists, economists, engineers, and product leaders to innovate on behalf of our customers and help turn generative AI shopping into Amazon’s next business pillar. Key job responsibilities As the Principal Economist in the Shopping Economics team, you are a senior member of the technical leadership team, working with executives, principal engineers and scietists, and senior product leaders. Your economic thought leadership helps us to build new-to-world customer experiences that solve important problems for customers while creating new business models, ensuring Amazon is optimizing its innovation portfolio to maximally help customers solve their shopping problems. Solving problems like improving the match quality between customers’ heterogeneous needs and Amazon’s nearly infinite selection, articulating the economics of advertising in a conversation, using insights from economics to better align the LLM, and using deep learning techniques to measure substitution patterns and the economic value of engagement. You work with economists, scientists, and engineers Amazon-wide to rethink systems across the company to better optimize for helping customers through their entire shopping journey. You also develop and evangelize new mental models and new ways to measure the economic value of bleeding edge generative AI. As the senior economist in the team, you also guide the work and careers of other economists on the team.
US, CA, Palo Alto
The Amazon Search team creates powerful, customer-focused search and advertising solutions and technologies. Whenever a customer visits an Amazon site worldwide and types in a query or browses through product categories, our services go to work. We design, develop, and deploy high performance, fault-tolerant distributed search systems used by millions of Amazon customers every day. This position will develop economic frameworks for selecting products into customer consideration sets, develop a theoretic framework of the search process and customer frictions that lends to policy evaluation, and create frameworks for coordinating product discovery with other marketplace decision systems like ordering, pricing, and delivery optimization. The ideal candidate will have outstanding Economics knowledge, demonstrated strength in practical and policy relevant structural econometrics, strong collaboration skills, proven ability to lead highly ambiguous and large projects, and a drive to deliver results. They will work closely with Economists, Data / Applied Scientists, Engineers, and Product leads to integrate economic insights into policy and production systems Familiarity with informational retrieval and recommender systems is a plus but not required. Key job responsibilities This role is responsible for creating mechanisms (metrics, models, mechanism) that optimize search while accounting for effects on the entirety of the Amazon Stores. Some example projects include: * Develop an economic frameworks for selecting products into customer consideration sets. Utilizing demand estimation, internalizing spillovers (e.g. menu effects), and incorporating long term effects on customer beliefs. We want to embed economics into state of the art list-wise ranking models. * Develop a means of valuing newly launched products and how the impact all aspects of the experience (prices, brand awareness, or even referential utility). * Develop a theoretic framework of the search process with a valuation of customer frictions that lends to evaluation of changes in the experience (aka a “search/browse model”) * Create frameworks for coordinating product discovery with other marketplace decision systems like ordering, pricing, and delivery optimization.