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Economics

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

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  • 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
  • Yao Zhao, Kwang-Sung Jun, Bibek Adhikari, Tanner Fiez, Lalit Jain
    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
  • 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

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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
US, WA, Seattle
The Impact Intelligence team solves economic problems related to pricing and promotions for Amazon's retail website. We are seeking an experienced, high-energy Economist to help envision, design and build the next generation of pricing systems and promotions models. 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 to our customers. Key job responsibilities 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 with the business systems that Amazon uses in pricing and promotions logic. You should be familiar with modern tools for data science and business analysis, have experience coding with engineers to put projects into production, and have an ability to communicate effectively with business leaders. We are particularly interested in candidates with research background in applied microeconomics, econometrics, and/or statistical inference. 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 and for promotions systems. The team uses world-class machine learning and econometric modeling to make sure that prices and promotions at Amazon are aligned with Amazon’s customer-first mentality. We are open to hiring candidates to work out of one of the following locations: Cupertino, CA, USA | Seattle, WA, USA
US, WA, Seattle
The Impact Intelligence team solves economic problems related to pricing and promotions for Amazon's retail website. We are seeking an experienced, high-energy Economist to help envision, design and build the next generation of pricing systems and promotions models. 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 to our customers. Key job responsibilities 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 with the business systems that Amazon uses in pricing and promotions logic. You should be familiar with modern tools for data science and business analysis, have experience coding with engineers to put projects into production, and have an ability to communicate effectively with business leaders. We are particularly interested in candidates with research background in applied microeconomics, econometrics, and/or statistical inference. 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 and for promotions systems. The team uses world-class machine learning and econometric modeling to make sure that prices and promotions at Amazon are aligned with Amazon’s customer-first mentality. We are open to hiring candidates to work out of one of the following locations: Cupertino, CA, USA | Seattle, WA, USA
US, WA, Seattle
Amazon’s Customer Behavior Analytics org is looking for an Economist to spearhead the rapid growth of our Marketing Measurement solutions. The team focuses on building scalable ML and causal inference solutions to estimate the effectiveness of Amazon marketing efforts and provide actionable insights to the various marketing teams within Amazon. We work closely with business stakeholders and strive to continuously produce tangible impact on the company’s strategic and tactical planning and operations. A successful candidate will be a self-starter, comfortable with ambiguity, able to think big and be creative, while still paying careful attention to detail. You will apply your econometrics expertise to identify opportunities for further research and to provide insights that drive larger initiatives. You should be able to translate how data represents the customer journey, be comfortable dealing with large and complex data sets, and have experience using machine/deep learning at scale to solve business problems. You should have strong analytical and communication skills, be able to work with product managers and software teams to define key business questions and work with the analytics team to solve them. You will join a highly collaborative and diverse working environment that will empower you to shape the future of Amazon marketing, as well allow you to be part of the large science community within the Customer Behavior Analytics (CBA) organization. Key job responsibilities The main responsibilities for this position include: - Apply your expertise in causal modeling and ML to develop systems that describe how Amazon’s marketing campaigns impact customers’ actions - Own the end-to-end development of novel causal inference models that address the most pressing needs of our business stakeholders and help guide their future actions - Improve upon and simplify our existing solutions and frameworks - Review and audit modeling processes and results from other economists/scientists, both junior and senior - Work with marketing leadership to align our measurement plan with business strategy - Formalize assumptions about how our models are expected to behave and explain why they are reasonable - Identify new opportunities that are suggested by the data insights - Bring a department-wide perspective into decision making - Develop and document scientific research to be shared with the greater science community at Amazon About the team The Customer Behavior Analytics (CBA) organization owns Amazon’s insights pipeline, from data collection to deep analytics. We aspire to be the place where Amazon teams come for answers, a trusted source for data and insights that empower our systems and business leaders to make better decisions. Our outputs shape Amazon product and marketing teams’ decisions and thus how Amazon customers see, use, and value their experience. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA
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 machine learning, causal inference, and econometrics skills to join our cross-domain group of economists, applied scientists, research scientists, and data scientists. As a Senior Economist, you will be part of a high-impact team designing and implementing cutting edge machine learning and causal models, incentive mechanisms, experiments to evaluate and (re)design new products and policies, quantify the impact of FBA workflows, seller recommendations, and information on seller decisions and outcomes, while collaborating with business and software teams to solve key challenges 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 machine learning and causal models at scale to solve diverse and complex economic/business problems faced in seller inventory and capacity management systems. - Provide data-driven guidance on strategic questions facing the FBA leadership. - Design and conduct experiments to validate theories and improve understanding of Amazon's third-party seller ecosystem. - 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. We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA
US, NY, New York
Amazon.com is seeking an exceptional Senior Economist to join our Advertising Finance team. As a tech lead of the Adpt Finance Econ and Science team, you will play a pivotal role in answering critical questions that drive the long-term strategy of our advertising business. These questions include: - What are the long-term impacts of our initiatives? - Where will Advertising’s growth come from in the next year? - How big will the Advertising business become over the next three years? - What are the interactions between consumers and the Ads business? At Amazon, we're always finding answers that redefine industries. In this Senior Economist role, you'll have the unique opportunity to collaborate with top-tier talent, influence senior leadership, and make a tangible impact on the future of advertising. If you're passionate about pushing the boundaries of economic research, thrive on challenging modeling puzzles, and crave a dynamic environment where your insights directly shape business strategy, this is the role for you. Key job responsibilities - Lead causal analysis projects as the primary technical expert, guiding the team in applying advanced economic methodologies to solve complex business challenges. - Collaborate closely with economists, data scientists, financial managers, and business leaders to define product requirements, offer scientific support, and effectively communicate feedback throughout project lifecycles. - Utilize programming languages such as Python, R, Scala, etc., to implement sophisticated economics methods tailored to address specific business problems, ensuring robustness and scalability. - Drive continuous improvement by innovating existing methodologies, including developing new data sources, rigorously testing model enhancements, and fine-tuning model parameters to optimize performance and accuracy. - Present data and insights in a clear, actionable format, enabling stakeholders to make informed decisions and address critical business questions with confidence. We are open to hiring candidates to work out of one of the following locations: New York, NY, USA | Seattle, WA, USA
US, WA, Seattle
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: New York City, NY, USA | San Francisco, CA, USA | Santa Monica, CA, USA | Seattle, WA, USA
US, WA, Bellevue
Economists at Amazon will be expected to work directly with our Chief Economists and senior management on key business problems faced in retail, international retail, cloud computing, third party merchants, search, Kindle, streaming video, and operations. Amazon economists will apply the frontier of economic thinking to market design, pricing, forecasting, program evaluation, online advertising and other areas. You will build econometric models, using our world class data systems, and apply economic theory to solve business problems in a fast moving environment. 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. Amazon.com strives to be Earth's most customer-centric company where people can find and discover anything they want to buy online. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. About the team The SCOT Lab (Supply Chain Optimization Technology Lab) team is responsible for designing and implementing systems to measure the impact of SCOT initiatives. We're currently seeking an economist to drive innovation within SCOT, which involves developing novel scientific approaches and advancing our system further upstream in the innovation process. We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA
US, WA, Bellevue
Where will Amazon's growth come from in the next year? What about over the next five? Which product lines are poised to quintuple in size? Are we investing enough in our infrastructure, or too much? How do our customers react to changes in prices, product selection, or delivery times? These are among the most important questions at Amazon today. The Topline Forecasting team in the Supply Chain Optimization Technologies (SCOT) group is looking for innovative, passionate and results-oriented Principal Economist to provide thought-leadership to help answer these questions. You will have an opportunity to own the long-run outlook for Amazon’s global consumer business and shape strategic decisions at the highest level. The successful candidate will be able to formalize problem definitions from ambiguous requirements, build econometric models using Amazon’s world-class data systems, and develop cutting-edge solutions for non-standard problems. Key job responsibilities - You understand the state-of-the-art in time series and econometric modeling. - You apply econometric tools and theory to solve business problems in a fast moving environment. - You excel at extracting insights and correct interpretations from data using advanced modeling techniques. - You communicate insights in a digestible manner to senior leaders in Finance and Operations within the company. - You are able to anticipate future business challenges and key questions, and have the ability to design modeling solutions to tackle them. - You have broad influence over the Topline team’s scientific research agenda and deliverables. - You contribute to the broader Econ research community in Amazon. - You advise other economists on scientific best-practices and raise the bar of research. - You will actively mentor other scientists and contribute to their career development. We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA | New York, NY, USA
US, WA, Seattle
Amazon Stores-Advertising Science Team is looking for an Economist to help translate cutting-edge causal inference, structural methods, and machine learning research into production solutions. The individual will have the opportunity to shape the technical and strategic vision of team projects, drive implementation of scientific models in production at scale, and deliver measurable business impact via cross-team and cross-functional collaboration. The mission of the Stores-Advertising Science Team is to foster value-generating flywheel for Amazon shoppers and sellers. We specialize in measuring and modeling the short- and long-term behavior of shoppers and sellers in relation to advertising and marketing, using state-of-the-art econometric and machine learning techniques. With a broad mandate to experiment and innovate, we are constantly advancing our scientific methodology and infrastructure to accelerate learnings and scale impact. Key job responsibilities - Develop econometric and machine learning models to optimize advertising and marketing strategies on behalf of our customers - Design, implement (in collaboration with engineers), and analyze experiments to verify the efficacy of different scientific solutions in production - Partner with cross-team technical contributors (scientists, software engineers, product managers) to drive improvement of scientific models in production - Write effective business narratives and scientific papers to communicate to both business and technical audiences, including the most senior leaders in the company We are open to hiring candidates to work out of one of the following locations: Los Angeles, CA, USA | New York City, NY, USA | Seattle, WA, USA