Newsletter
Follow Us
Economics.svg
Research Area

Economics

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

Recent publications

View All View All
  • 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
  • Extracting structured labor market information from job postings with generative ai
    Mark Howison, Will Ensor, Suraj Maharjan, Rahil Parikh, Srinivasan Sengamedu, "SHS", Paul Daniels, Amber Gaither, Carrie Yeats, Chandan Reddy, Justine Hastings
    ACM Digital Government Research and Practice (DGOV)
    2024
    Labor market information is an important input to labor, workforce, education, and macroeconomic policy. However, granular and real-time data on labor market trends are lacking; publicly available data from survey samples are released with significant lags and miss critical information such as skills and benefits. We use generative Artificial Intelligence to automatically extract structured labor market
    Economics
Load more

Related content

Load more

Work with us

See more jobs See more jobs
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.
Senior Economist, Catalog Experimentation and Impact Measurement
US, WA, Seattle
This position gives you an opportunity to conceptualize an Amazon wide program from scratch If that rings a bell and if you possess the confidence to navigate through early stage ambiguities, read on. Amazon Selection and Catalog Systems (ASCS) builds the systems that host and run the world’s largest e-Commerce products catalog - it powers the online buying experience for customers worldwide so they can find, discover and buy anything they want. Amazon’s customers rely on the completeness, consistency and correctness of Amazon's product data to make well-informed purchase decisions. Improving the quality of product data is a continuous process. It requires data driven decisions on what product data changes simplify and improve the Customers’ experience. Our team seeks a Sr. Economist with demonstrated experience of applying causal inference at scale. Our problems include attributing values to actions in complex world of catalog information driving customer behavior. The ideal candidate combines acumen in data science and causal modeling to grapple with these and other challenges and guide decision-making at the highest levels. This is an opportunity to influence catalog quality improvements across Amazon.
Economist I, Global Media & Entertainment Economics
US, WA, Seattle
Amazon’s Global Media and Entertainment (GME) organization is creating a future of entertainment where creative content, innovation, and commerce come together. We leverage Amazon’s unique expertise across video, music, gaming, and more to create a truly immersive entertainment experience. Our team, GME Science, is focused on building science tools to optimize Amazon’s entertainment offerings, so that we can provide a great customer experience while operating as a sustainable and profitable business. We push ourselves to Think Big, building ambitious models that create value in multiple GME businesses. This role will expand our team’s measurement work. Business leaders need to quickly understand the long-term impact of various investments, such as new website features, content creation, or marketing campaigns. Our team figures out how to take short-term signals – such as clicks or signups – and turn them into estimates of long-term financial impacts. The right way to design such a metric depends on how the metric will be used, e.g. for a backward-looking evaluation or a forward-looking estimate based on limited realtime signals. We work with measurement teams in each business as well as central teams to build foundational measurement science and adapt it for unique use cases. To be successful in this role, you will need effective communication, an ability to work closely with stakeholders across our many GME partner teams, and the skill to translate data-driven findings into actionable insights. This includes developing a deep understanding of our business context, which is ambiguous and can change quickly. Your work will be used by decision-makers across GME to deliver the best entertainment experience for our customers, which means we have a high bar. Our healthy team culture is supportive and fast-paced, and we prioritize learning, growth, and helping each other to continuously raise the bar. *Impact and Career Growth* In today’s entertainment landscape, critical decisions are made with data and economic models. You’ll help GME leaders ask the right questions, and then deliver data-driven answers, creating the future of GME at Amazon. You’ll help define a long-term science vision in this space and translate it into an actionable roadmap. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding – a perfect recipe for career growth as an economist in tech. Key job responsibilities • Design and build econometric models, especially causal models, to measure the value of the business and its many features • Develop science products from concept to prototype to production, incorporating feedback from scientists and business partners • Independently identify and pursue new opportunities to leverage economic insights across GME businesses • Write business and technical documents communicating business context, methods, and results to business leadership and other scientists • Serve as a technical reviewer for our team and related teams, including document and code reviews
Economist, Prime Video
US, WA, Seattle
Economists at Amazon partner closely with senior management, business stakeholders, scientist and engineers, and economist leadership to solve key business problems. As part of the Content Discovery and Experimentation Science team within Prime Video, you will leverage your expertise in causal inference and experimental design to make Prime Video the best-in-class digital video experience. Key job responsibilities - Build causal models and metrics that capture trade-off decisions when business and customer outcomes do not align - Partner with data scientists and product managers to integrate these metrics into Prime Video's experimentation tooling - Work with finance partners to ensure that the team's product metrics contribute to Prime Video's strategic business and financial objectives - Independently write technical and business documents to communicate ideas and proposals to various audiences - Educate and advocate for best practices in experimentation and how to use it for decision-making
Economist I, AWS Marketing Measurement
US, NY, New York
Amazon Web Services (AWS) is building a world-class marketing organization, and we are looking for an Economist to join the central data and science organization for AWS Marketing. This candidate will develop innovative solutions to measure the return on marketing investments. They will work closely with business leaders, scientists, and engineers to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of innovative measurement solutions. They will interact with functional leaders owning events (e.g. re:Invent, summits, webinars), paid media (paid search, paid social, display), AWS-owned channels (email, website, console) as well as lead management organization to drive the development, fine-tuning and adoption of the consistent measurement framework across these diverse initiatives. We seek candidates with an entrepreneurial spirit who want to make a big impact on AWS growth. They will develop strong working relationships and thrive in a collaborative team environment. They will have the creativity, curiosity, and strong judgment to work on high-impact, high-visibility products to improve the experience of AWS leads and customers. AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Mentorship & Career Growth: We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance: We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Inclusive Team Culture: Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Key job responsibilities -Apply your expertise in causal inference and ML to develop systems to measure B2B marketing impact -Develop and execute science products from concept, prototype to production incorporating feedback from customers, scientists and business leaders -Identify new opportunities for leveraging economic insights and models in the marketing space -Write technical white papers and business-facing documents to clearly explain complex technical concepts to audiences with diverse business/scientific backgrounds
Senior Economist, Fulfillment By Amazon
US, WA, Bellevue
The Fulfillment by Amazon (FBA) and Supply Chain by Amazon (SCA) enable third-party sellers to use Amazon’s world-class science and logistics infrastructure to supply and fulfill customers worldwide with unprecedented fast delivery promise to customer. In doing so, sellers spend more time building great products, delight customers and grow their business. The FBA team is looking for a Senior Economist with strong causal inference and econometrics skills to join our cross-domain group of economists, applied scientists, research scientists, and data scientists. This person will primarily focus on the new and exciting domain of SCA. As a Senior Economist, you will be part of a high-impact team building cutting edge economic and causal models, developing incentive and recommendation systems, conducting experiments to evaluate and (re)design products and policies, quantifying the impact of FBA and SCA workflows, as well as designing and evaluating economic mechanisms to address the information asymmetries between sellers and Amazon. This person will be collaborating closely with business and software teams to research, innovate, and solve high impact economics problems facing the worldwide FBA business. We are seeking someone who can thrive in a fast-paced, high-energy, and fun-to-work environment, where the team delivers value incrementally and frequently. We value highly technical people who know their subject matter deeply and are willing to learn new areas. We look for individuals who know how to deliver results and show a desire to develop themselves, their colleagues, and their careers. Key job responsibilities - Research and develop causal models at scale to solve diverse and complex economic/business problems faced in FBA/SCA inventory and capacity management systems. - Build economic, statistical, and predictive models to enhance our understanding of seller behavior, preferences, and dynamics. - Provide data-driven guidance on strategic SCA related policy and economic questions. - Propose innovative and rigorous ways of collecting data about our sellers’ expectations and actions to help developing new products and services for our sellers. - Design and conduct randomized experiments to validate theories and improve understanding of Amazon’s third-party seller ecosystem and supply chain. - Develop mechanisms to align millions of sellers’ decisions with those of customers’ needs through better coordinating inventory, inbound, and capacity related decisions. - Collaborate with product managers, scientists, and software developers to incorporate models into production processes and influence senior leaders. About the team Sellers play a vital role in Amazon’s ecosystem, integral to our mission of offering the Earth’s largest selection and lowest prices. FBA is a service that enables third-party sellers to outsource order fulfillment to Amazon, and leverage Amazon’s world-class facilities to provide customers Prime delivery promise. By partnering with Amazon, sellers benefit from powerful, cost-effective solutions that leverage our scale and technology, gain access to Prime members worldwide, increase their sales, and have more time to continue inventing amazing products for customers. With commitment to taking on even more of the supply chain and operational complexities on behalf of our selling partners, Amazon introduced Supply Chain by Amazon (SCA), an end-to-end, fully automated suite of supply chain services. This comprehensive solution empowers sellers to quickly and reliably transport products from manufacturing sites to customers worldwide. Amazon Warehousing and Distribution (AWD) is a pivotal service in SCA that provides best-in-class bulk storage and distribution services to sellers, ensuring they remain well-stocked across all their sale and fulfillment channels while reducing the total supply chain costs. The FBA team is the core group in charge of fulfillment, inventory management, pricing, and a diverse range of operational recommendation services for sellers, as well as building the internal resource management systems. We work to learn seller behavior, understand seller experience, build automated assistants to sellers, recommend right actions to sellers, design seller policies and incentives, and develop science products and services that empower third-party sellers to grow their businesses. To do so, we build and innovate science solutions at the intersection of machine learning, statistics, economics, operations research, and data analytics. We work full-stack, from foundational backend systems to future-forward user interfaces. Our culture is centered on rapid prototyping, rigorous experimentation, and data-driven decision-making.
Senior Economist, Survey Methods, People eXperience Technology Central Science (PXTCS)
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 Senior 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 teams of researchers 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. Key job responsibilities Use reduced-form causal analysis and/or structural economic modeling methods to evaluate the impact of change on employee outcomes.
Senior Economist, Private Brands Discovery
US, WA, Seattle
The Private Brands Discovery team designs innovative machine learning solutions to drive customer awareness for Amazon’s own brands and help customers discover products they love. Private Brands Discovery is an interdisciplinary team of Scientists and Engineers, who incubate and build disruptive solutions using cutting-edge technology to solve some of the toughest science problems at Amazon. To this end, the team employs methods from Natural Language Processing, Deep learning, multi-armed bandits and reinforcement learning, Bayesian Optimization, causal and statistical inference, and econometrics to drive discovery across the customer journey. Our solutions are crucial for the success of Amazon’s own brands and serve as a beacon for discovery solutions across Amazon. This is a high visibility opportunity for someone who wants to have business impact, dive deep into large-scale problems, enable measurable actions on the consumer economy, and work closely with scientists and engineers. As a scientist, you bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions.. With a focus on bias for action, this individual will be able to work equally well with Science, Engineering, Economics and business teams. Key job responsibilities - 5+ yrs of relevant, broad research experience after PhD degree or equivalent. - Advanced expertise and knowledge of applying observational causal interference methods - Strong background in statistics methodology, applications to business problems, and/or big data. - Ability to work in a fast-paced business environment. - Strong research track record. - Effective verbal and written communications skills with both economists and non-economist audiences.
Economist, PXT Central Science
US, VA, Arlington
The People eXperience and Technology Central Science Team (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. We are an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. We are looking for an economist who is able to work with business partners to hone complex problems into specific, scientific questions, and test those questions to generate insights. The ideal candidate will work with engineers and computer scientists to estimate models and algorithms on large scale data, design pilots and measure their impact, and transform successful prototypes into improved policies and programs at scale. We are looking for a creative thinker who can combine a strong technical economic toolbox with a desire to learn from other disciplines, and who knows how to execute and deliver on big ideas as part of an interdisciplinary technical team. Ideal candidates will work closely with business partners to develop science that solves the most important business challenges. They will work in a team setting with individuals from diverse disciplines and backgrounds. They will serve as an ambassador for science and a scientific resource for business teams, so that scientific processes permeate throughout the HR organization to the benefit of Amazonians and Amazon. Ideal candidates will own the data analysis, modeling, and experimentation that is necessary for estimating and validating models. They will work closely with engineering teams to develop scalable data resources to support rapid insights, and take successful models and findings into production as new products and services. They will be customer-centric and will communicate scientific approaches and findings to business leaders, listening to and incorporate their feedback, and delivering successful scientific solutions. Key job responsibilities Use causal inference methods to evaluate the impact of policies on employee outcomes. Examine how external labor market and economic conditions impact Amazon's ability to hire and retain talent. Use scientifically rigorous methods to test solutions for improving employee recognition. A day in the life Work with teammates to apply economic methods to business problems. This might include identifying the appropriate research questions, writing code to implement a DID analysis or estimate a structural model, or writing and presenting a document with findings to business leaders. Our economists also collaborate with partner teams throughout the process, from understanding their challenges, to developing a research agenda that will address those challenges, to help them implement solutions. About the team We are a multidisciplinary team that combines the talents of science and engineering to develop innovative solutions to make Amazon Earth's Best Employer.
Economist , Global Media & Entertainment Economics
US, WA, Seattle
Amazon’s Global Media and Entertainment (GME) organization is creating a future of entertainment where creative content, innovation, and commerce come together. We leverage Amazon’s unique expertise across video, music, gaming, and more to create a truly immersive entertainment experience. Our team, GME Science, is focused on building science tools to optimize Amazon’s entertainment offerings, so that we can provide a great customer experience while operating as a sustainable and profitable business. We push ourselves to Think Big, building ambitious models that create value in multiple GME businesses. This role will expand our team’s measurement work. Business leaders need to quickly understand the long-term impact of various investments, such as new website features, content creation, or marketing campaigns. Our team figures out how to take short-term signals – such as clicks or signups – and turn them into estimates of long-term financial impacts. The right way to design such a metric depends on how the metric will be used, e.g. for a backward-looking evaluation or a forward-looking estimate based on limited realtime signals. We work with measurement teams in each business as well as central teams to build foundational measurement science and adapt it for unique use cases. To be successful in this role, you will need effective communication, an ability to work closely with stakeholders across our many GME partner teams, and the skill to translate data-driven findings into actionable insights. This includes developing a deep understanding of our business context, which is ambiguous and can change quickly. Your work will be used by decision-makers across GME to deliver the best entertainment experience for our customers, which means we have a high bar. Our healthy team culture is supportive and fast-paced, and we prioritize learning, growth, and helping each other to continuously raise the bar. *Impact and Career Growth* In today’s entertainment landscape, critical decisions are made with data and economic models. You’ll help GME leaders ask the right questions, and then deliver data-driven answers, creating the future of GME at Amazon. You’ll help define a long-term science vision in this space and translate it into an actionable roadmap. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding – a perfect recipe for career growth as an economist in tech. Key job responsibilities • Design and build econometric models, especially causal models, to measure the value of the business and its many features • Develop science products from concept to prototype to production, incorporating feedback from scientists and business partners • Independently identify and pursue new opportunities to leverage economic insights across GME businesses • Write business and technical documents communicating business context, methods, and results to business leadership and other scientists • Serve as a technical reviewer for our team and related teams, including document and code reviews
See more jobs
View from space of a connected network around planet Earth representing the Internet of Things.
Get more from Amazon Science
Subscribe to our monthly newsletter

Amazon.com | Conditions of Use | Privacy | © 1996-2025 Amazon.com, Inc. or its affiliates

Follow Us