Research Area


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)
    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
  • 2023 Conference on Digital Experimentation @ MIT (CODE@MIT)
    There are many experimental settings that may suffer from cross-unit (customers, seller, advertiser, etc.) spillovers, for instance through network effects. Such effects introduce bias and prevent the experimenter from drawing trustworthy insights on the data. One approach to dealing with such spillovers is to group units into clusters and randomize treatment status at the cluster level. Examples of clusters
  • Hamidreza Habibollahi Najaf Abadi, Maxim Nikiforov, Aaron Krive, Jeffrey W. Herrmann, Mohammad Modarres
    ESREL 2023
    Enabling a circular economy aims to reduce the amount of global waste generated from electrical and electronic equipment, mitigate the associated risk to the ecosystem and human health, and address concerns over limited material resources. Durability is a critical concern because keeping products in use for a longer time should reduce resource consumption and waste. Assessing the durability of products
  • KDD 2023 Workshop on Causal Inference and Machine Learning in Practice: Use cases for Product, Brand, Policy and Beyond
    We introduce OpportunityFinder, a code-less framework for performing a variety of causal inference studies with panel data for non-expert users. In its current state, OpportunityFinder only requires users to provide raw observational data and a configuration file. A pipeline is then triggered that inspects/processes data, chooses the suitable algorithm(s) to execute the causal study. It returns the causal
  • Applied Marketing Analytics (AMA)
    Brands usually invest in a portfolio of digital ad products for brand consideration and conversion, and their performance is commonly evaluated with ad - attributed metrics. However, these metrics limit the measurement of advertising effectiveness within a short time window, typically of two weeks. Therefore, they could underestimate the total effect if some ad products' efficacy lasts beyond the measurement

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US, WA, Seattle
Amazon's Global Fixed Marketing Campaign Measurement & Optimization (CMO) team is looking for a senior economic expert in causal inference and applied ML to advance the economic measurement, accuracy validation and optimization methodologies of Amazon's global multi-billion dollar fixed marketing spend. This is a thought leadership position to help set the long-term vision, drive methods innovation, and influence cross-org methods alignment. This role is also an expert in modeling and measuring marketing and customer value with proven capacity to innovate, scale measurement, and mentor talent. This candidate will also work closely with senior Fixed Marketing tech, product, finance and business leadership to devise science roadmaps for innovation and simplification, and adoption of insights to influence important resource allocation, fixed marketing spend and prioritization decisions. Excellent 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. Key job responsibilities - Advance measurement, accuracy validation, and optimization methodology within Fixed Marketing. - Motivate and drive data generation to size. - Develop novel, innovative and scalable marketing measurement techniques and methodologies. - Enable product and tech development to scale science solutions and approaches. A day in the life - Propose and refine economic and scientific measurement, accuracy validation, and optimization methodology to improve Fixed Marketing models, outputs and business results - Brief global fixed marketing and retails executives about FM measurement and optimization approaches, providing options to address strategic priorities. - Collaborate with and influence the broader scientific methodology community. About the team CMO's vision is to maximizing long-term free cash flow by providing reliable, accurate and useful global fixed marketing measurement and decision support. The team measures and helps optimize the incremental impact of Amazon (Stores, AWS, Devices) fixed marketing investment across TV, Digital, Social, Radio, and many other channels globally. This is a fully self supported team composed of scientists, economists, engineers, and product/program leaders with S-Team visibility. We are open to hiring candidates to work out of one of the following locations: Irvine, CA, USA | San Francisco, CA, USA | Seattle, WA, USA | Sunnyvale, CA, USA
US, NY, New York
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 Economists to 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 econometrics models using Amazon’s world-class data systems, and develop cutting-edge solutions for non-standard problems. Key job responsibilities · Develop new econometric models or improve existing approaches using scalable techniques. · Extract data for analysis and model development from large, complex datasets. · Closely work with engineering teams to build scalable, efficient systems that implement prototypes in production. · Apply economic theory to solve business problems in a fast moving environment. · Distill problem definitions from informal business requirements and communicate technical solutions to senior business leaders. · Drive innovation and best practices in applied research across the Amazon research science community. We are open to hiring candidates to work out of one of the following locations: New York, NY, USA
US, MD, Virtual Location - Maryland
We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to work with large and complicated data sets. Some knowledge of econometrics, as well as basic familiarity with Python is necessary, and experience with SQL and UNIX would be a plus. This is a part time position, 29 hours per week, with compensation being awarded on an hourly basis. You will learn how to build data sets and perform applied econometric analysis at Internet speed collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. Roughly 85% of previous cohorts have converted to full time economics employment at Amazon. If you are interested, please send your CV to our mailing list at We are open to hiring candidates to work out of one of the following locations: Virtual Location - MD
US, TX, Austin
Come be a part of a rapidly expanding $35 billion dollar global business. At Amazon Business, a fast-growing startup passionate about building solutions, we set out every day to innovate and disrupt the status quo. We stand at the intersection of tech & retail in the B2B space developing innovative purchasing and procurement solutions to help businesses and organizations thrive. At Amazon Business, we strive to be the most recognized and preferred strategic partner for smart business buying. Bring your insight, imagination and a healthy disregard for the impossible. Join us in building and celebrating the value of Amazon Business to buyers and sellers of all sizes and industries. Unlock your career potential. The Business Prime team is looking for a talented Economist with well rounded set of capabilities to help manage our ever growing need for analysis of increasingly complex business questions. At Amazon, understanding customer data is paramount to our success in providing customers with relevant and enticing benefits as well as an expanding set of propositions internationally. You will be working in one of the worlds’ largest and most exciting big-data environments. The Economist role occupies a unique space at the intersection of technology, machine-learning, econometrics, large-scale scientific computing, social science, and product management. In this role, you will be the thought leader on the economic underpinnings of the Business Prime program, influence stakeholders across function and at senior levels of Amazon, engage with SDM counterparts to build the technology solution to serve customers, and with partner with marketing on campaigns optimized to maximize value for customers and Amazon. The ideal candidate will need to understand business problems and turn them into useful analyses and recommendations. They will communicate complicated concepts clearly to business leaders and other scientists, have a desire to make a large business impact for customers using econometrics, data science and strong execution and completion skills for major, highly-visible strategic projects under fast-paced business deadlines. The role involves both building data products, i.e. automated and productionized models at scale, as well as pricing, plan structure, benefits/proposition, and other strategic decisions including customer churn reduction. Amazon Business ( is an online store that combines the selection, convenience and value customers have come to know and love from Amazon, with new features and unique benefits tailored to the needs of businesses. Amazon Business provides easy access to hundreds of millions of products – everything from IT and lab equipment to education and food-service supplies. Amazon Business customers also enjoy a variety of benefits, including business-only pricing and selection, a multi-seller marketplace, single- or multi-user business accounts, Business Prime, approval workflow, purchasing system integrations, payment solutions, tax exemptions, dedicated customer support and more. Business Prime is a paid subscription service for verified business, charity or government organizations that provides the familiar Prime shopping experience end users love at home, with pricing plans and benefits that are suited for work. Business Prime now serves customers throughout the world, with a tiered pricing model currently based on number of users, and associated benefits with different willingness to pay and cost to serve profiles. Our customers range from government entities with tens of thousands of users to sole proprietors, each with different micro-economic characteristics. We are open to hiring candidates to work out of one of the following locations: Austin, TX, USA | Seattle, WA, USA
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, 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, 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, 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