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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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  • Comparing two samples of data, we observe a change in the distribution of an outcome variable. In the presence of multiple explanatory variables, how much of the change can be ex-plained by each possible cause? We develop a new estimation strategy that, given a causal model, combines regression and re-weighting methods to quantify the contribution of each causal mechanism. Our proposed methodology is multiply
  • 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
  • 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
  • 2023 Conference on Digital Experimentation @ MIT (CODE@MIT)
    2023
    In this study, we aim to present an effective methodology tailored for companies interested in implement-ing adaptive experimentation in scenarios characterized by potential selection biases or endogeneity. To illustrate our approach, we begin by delving into the realm of online experimentation. Online platforms routinely conduct thousands of A/B tests annually to gain insights into the impact of user-facing
  • 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

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US, WA, Seattle
WWGS (Worldwide Grocery Stores) organization leads the innovation of Amazon’s omni-channel grocery offerings (Fresh, Whole Foods, 3P). In this space, Amazon aims to delight customers by providing broad selection, competitive prices, best-in-class delivery, convenient in-store/pickup options across regions, and an end-to-end shopping experience that makes it easy for customers to discover what they love and build complete grocery baskets. The Grocery Economics and Optimization team in WWGS is looking for an Economist to help create and drive the long-term vision for how we manage selection of products for our grocery brands globally. As an Economist on our team, you will work with product managers, vendor managers, software development engineers (SDEs), and other scientists to help the grocery organization determine optimal selection for our online and physical stores. You will develop and extend models of key customer behavior and preferences such as substitutability/complementarity of products, expected demand, and optimization approaches that produce selection recommendations that delight our customers and meet our real-world constraints. You will be expected to own the the full lifecycle of your projects from devising methodological approaches, implementation, validation, and working with SDEs to integrate into production systems. A successful candidate will be able to partner effectively with both business and technical teams, including clear communication of results and the ability to influence a variety of stakeholders. They will be an expert in machine learning and operations research. The role will also include running experiments to validate developed approaches. Key job responsibilities - Interact with engineering, operations, science, and business teams to develop an understand and domain knowledge of processes, system architectures, and business requirements. - Develop scalable models to generate selection models. - Create prototypes, simulations, and experiments to test devised solutions. - Advocate technical solutions to business stakeholders, engineering teams, and executive-level decision makers - Work closely with engineers to integrate models into production systems. 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: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan About the team The WW Grocery Stores team has a broad charter spanning multiple banners worldwide – Amazon Fresh, Amazon Go, Whole Foods, and third party grocery partnerships. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA
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 Principal 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. We are open to hiring candidates to work out of one of the following locations: Austin, TX, USA | Los Angeles, CA, USA | New York City, NY, USA | Seattle, WA, USA
US, WA, Seattle
We’re looking for an economist who’s excited to help make the AWS sales team as effective as possible. You’ll help us determine the impacts of sales coverage, training, compensation, and more on the activity of AWS’s customers. Key job responsibilities - lead customer meetings - design and implement research studies - coordinate support from data, engineering, product, and other science teams About the team We’re a widely distributed team of economists and applied scientists nested in a larger organization that provides data and PM support to us. We focus on improving major AWS Sales processes, such as territory construction, sales coverage, compensation policy, training programs, etc. Our partners are generally the business units that own these processes as well as Finance. We use a wide range of econometric and ML methods to help deliver the best recommendations to our customers – and we’re open to new methods should you want to try one! We are open to hiring candidates to work out of one of the following locations: Dallas, TX, USA | Seattle, WA, USA
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 economists who are able to apply economic methods to address business problems. 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 creative thinkers who can combine a strong technical economic toolbox with a desire to learn from other disciplines, and who know how to execute and deliver on big ideas as part of an interdisciplinary technical team. Ideal candidates will work in a team setting with individuals from diverse disciplines and backgrounds. They will work with teammates to develop scientific models and conduct 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. 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. We are open to hiring candidates to work out of one of the following locations: Arlington, VA, USA | Boston, MA, USA | New York, NY, USA | Seattle, WA, USA
US, WA, Seattle
We are seeking a senior scientist with demonstrated experience in A/B testing along with related experience with observational causal modeling (e.g. synthetic controls, causal matrix completion). Our team owns "causal inference as a service" for the Pricing and Promotions organization; we run A/B tests on new pricing algorithms and, where experimentation is impractical, conduct observational causal studies. Key job responsibilities We are seeking a senior scientist to help envision, design and build the next generation of pricing capabilities behind Amazon’s on-line retail business. On our team, you will work at the intersection of economic theory, statistical inference, and machine learning to design and implement in production new methods and pricing strategies to deliver game changing value for our customers. This position is perfect for someone who has a deep and broad analytic background, is passionate about using mathematical modeling and statistical analysis to make a real difference. You should be familiar with modern tools for data science and business analysis and have experience coding with engineers to put projects into production. We are particularly interested in candidates with research background in experimental statistics. A day in the life -Discuss with business problems with business partners, product managers, and tech leaders -Brainstorm with other scientists to design the right model for the problem at hand -Present the results and new ideas for existing or forward looking problems to leadership -Dive deep into the data -Build working prototypes of models -Work with engineers to implement prototypes in production -Analyze the results and review with partners About the team We are a team of scientists who design and implement the analytics powering pricing for Amazon’s on-line retail business. We use world-class analytics to make sure that the prices for all of Amazon’s goods and services are aligned with Amazon’s corporate goals. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA
US, CA, San Francisco
The Global Cross-Channel and Cross- Category Marketing (XCM) org are seeking an experienced Economist to join our team. XCM’s mission is to be the most measurably effective and creatively breakthrough marketing organization in the world in order to strengthen the brand, grow the business, and reduce cost for Amazon overall. We achieve this through scaled campaigning in support of brands, categories, and audiences which aim to create the maximum incremental impact for Amazon as a whole by driving the Amazon flywheel. This is a high impact role with the opportunities to lead the development of state-of-the-art, scalable models to measure the efficacy and effectiveness of a new marketing channel. In this critical role, you will leverage your deep expertise in causal inference to design and implement robust measurement frameworks that provide actionable insights to drive strategic business decisions. Key Responsibilities: - Develop advanced econometric and statistical models to rigorously evaluate the causal incremental impact of marketing campaigns on a new marketing channel - Collaborate cross-functionally with marketing, product, data science and engineering teams to define the measurement strategy and ensure alignment on objectives. - Leverage large, complex datasets to uncover hidden patterns and trends, extracting meaningful insights that inform marketing optimization and investment decisions. - Work with engineers, applied scientists and product managers to automate the model in production environment. - Stay up-to-date with the latest research and methodological advancements in causal inference, causal ML and experiment design to continuously enhance the team's capabilities. - Effectively communicate analysis findings, recommendations, and their business implications to key stakeholders, including senior leadership. - Mentor and guide junior economists, fostering a culture of analytical excellence and innovation. Qualifications: - Advanced degree (Ph.D. preferred) in Economics, Statistics, or a related quantitative field. - Minimum 7+ years of relevant experience in applying causal inference techniques, such as double machine learning, synthetic control, difference-in-differences, instrumental variables, and randomized experiments. - Proven track record of developing and implementing sophisticated, scalable models to measure marketing effectiveness and attribution. - Expertise in programming languages (e.g., R, Python) and proficiency in working with large, complex datasets. - Strong problem-solving skills, ability to think critically, and a keen eye for detail. - Excellent communication and presentation skills, with the ability to translate technical analyses into actionable business insights. - Experience in a fast-paced, data-driven environment, with the flexibility to adapt to changing business needs. A day in the life We are open to hiring candidates to work out of one of the following locations: San Francisco, CA, USA
US, WA, Seattle
Amazon's Weblab team enables experimentation at massive scale to help Amazon build better products for customers. A/B testing is in Amazon's DNA and we're at the core of how Amazon innovates on behalf of customers. We are seeking a skilled Economist to help us build the future of experimentation systems at Amazon. About you: You have an entrepreneurial spirit and want to make a big impact on Amazon and its customers. You enjoy enabling intelligent decisions in the face of real-world, noisy data, and have a bias for delivering simple solutions to complex problems. You're a scientist looking for a career where you'll be able to build, to deliver, and to impress. You're a thought leader and you demonstrate this by delivering solutions, not just by having ideas. You challenge yourself and others to come up with better solutions. You develop strong working relationships and thrive in a collaborative and friendly team environment. About us together: We're going to help Amazon innovate faster and smarter by designing and delivering the next generation of data analysis tools and visualizations. Along the way, we're going to face seemingly insurmountable challenges. We're going to argue about how to solve them, and we'll work together to find a solution that is better than each of the proposals we came in with. We'll make tough decisions, but we'll all understand why. We'll be the dream team. We have decades of combined experience on the team in many areas of data science so it's a great environment in which to learn and grow. Many of us have university teaching experience and we're happy to teach. But, we're also like children playing at the edge of a vast unexplored territory; we have a lot to learn and we are all exploring together with a sense of awe and humility. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA
US, WA, Seattle
This role will contribute to developing the Economics and Science products and services in the Fee domain, with specialization in supply chain systems and fees. Through the lens of economics, you will develop causal links for how Amazon, Sellers and Customers interact. You will be a key and senior scientist, advising Amazon leaders how to price our services. You will work on developing frameworks and scaleable, repeatable models supporting optimal pricing and policy in the two-sided marketplace that is central to Amazon's business. The pricing for Amazon services is complex. You will partner with science and technology teams across Amazon including Advertising, Supply Chain, Operations, Prime, Consumer Pricing, and Finance. We are looking for an experienced Principal Economist to improve our understanding of seller Economics, enhance our ability to estimate the causal impact of fees, and work with partner teams to design pricing policy changes. In this role, you will provide guidance to scientists to develop econometric models to influence our fee pricing worldwide. You will lead the development of causal models to help isolate the impact of fee and policy changes from other business actions, using experiments when possible, or observational data when not. Key job responsibilities 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, Strategy Analysts, Data Engineers, and Product leads to integrate economic insights into policy and systems production. Familiarity with systems and services that constitute seller supply chains is a plus but not required. About the team The Stores Economics and Sciences team is a central science team that supports Amazon's Retail and Supply Chain leadership. We tackle some of Amazon's most challenging economics and machine learning problems, where our mandate is to impact the business on massive scale. We are open to hiring candidates to work out of one of the following locations: San Francisco, CA, USA | Seattle, WA, USA
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. We are looking for a dynamic, resourceful, and organized Economist to join the Returns and Recommerce organization to develop new, data-driven solutions to support the most critical components of this rapidly scaling team. The Amazon R&R team has an opening for applied micro, empirical IO, and time series and forecasting with demonstrated industry, policy, or academic experience. You will apply economic theory to build econometric models, and prototype and put into production scalable implementations in partnership with technical teams, using Amazon’s world class data systems. You will be expected to be a thought leader as we chart new courses with our customer delivery support technologies. Successful candidates will have a deep knowledge of quantitative modelling in at least one area (ML, forecasting/time series, optimization, causal modeling), the ability to build and refine models that can be implemented in production, the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers, and the excitement to take iterative approaches to tackle big, long-term problems. Economists at Amazon will be expected to develop new techniques to process large data sets, address quantitative problems, and contribute to design of automated systems around the company. The economics community at Amazon has grown tremendously in the past few years – economists in Amazon R&R partner with economists company-wide to tackle some of the hardest problems at Amazon. As part of the R&R organization, you’ll partner closely with Science, Product, Tech, and Program teams to design innovative solutions to organizational and business problems, communicating highly complex findings to multiple audiences. The ability to understand and measure policy effects and then integrate them into downstream optimization systems is a highly valuable asset. You may come from any one of a variety of econometric backgrounds, but you must be comfortable with multiple modeling techniques, be able to acquire new techniques with practice, and be willing to show flexibility in finding the right technique to match the research problem. Our economists will be comfortable with both ambiguity and autonomy, and excel at investigative analyses. Key job responsibilities Key Responsibilities: - Conceptualize and lead global research initiatives in the Returns and Recommerce space - Guide the technical approach for the design and implementation of successful models and algorithms in support of expert cross-functional teams delivering on demanding projects - Conduct, direct, and coordinate all phases of research projects, demonstrating skill in all stages of the analysis process, including defining key research questions, recommending measures, working with multiple data sources, evaluating methodology and design, executing analysis plans, interpreting and communicating results - Functionally decompose complex problems into simple, straight-forward solutions We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA
US, VA, Arlington
Device Economics is looking for an economist experienced in causal inference, empirical industrial organization, forecasting, and scaled systems to work on business problems to advance critical resource allocation and pricing decisions in the Amazon Devices org. Output will be included in scaled systems to automate existing processes and to maximize business and customer objectives. Amazon Devices designs and builds Amazon first-party consumer electronics products to delight and engage customers. Amazon Devices represents a highly complex space with 100+ products across several product categories (e-readers [Kindle], tablets [Fire Tablets], smart speakers and audio assistants [Echo], wifi routers [eero], and video doorbells and cameras [Ring and Blink]), for sale both online and in offline retailers in several regions. The space becomes more complex with dynamic product offering with new product launches and new marketplace launches. The Device Economics team leads in analyzing these complex marketplace dynamics to enable science-driven decision making in the Devices org. Device Economics achieves this by combining economic expertise with macroeconomic trends, and including both in scientific applications for use by internal analysts, to provide deep understanding of customer preferences. Our team’s outputs inform product development decisions, investments in future product categories, product pricing and promotion, and bundling across complementary product lines. We have achieved substantial impact on the Devices business, and will achieve more. Device Economics seeks an economist adept in measuring customer preferences and behaviors with proven capacity to innovate, scale measurement, and drive rigor. The candidate will work with Amazon Devices science leadership to refine science roadmaps, models, and priorities for innovation and simplification, and advance adoption of insights to influence important resource allocation and prioritization decisions. Effective communication skills (verbal and written) are required to ensure success of this collaboration. The candidate must be passionate about advancing science for business and customer impact. We are open to hiring candidates to work out of one of the following locations: Arlington, VA, USA | Seattle, WA, USA