ARA Program Rules

Last updated: March 26, 2025

By applying to or participating in the Amazon Research Awards Program (the “ARA Program”), you (defined below) agree to the following rules (“Rules”). These Rules are solely between Amazon.com, Inc. and its affiliates (“Amazon”, “we”, “us”, or “our”) and the entity that you represent (“you” or “your”), including the lead researcher/s who applies to the ARA Program (the “Principal Investigator”) and any members of the research team. Capitalized terms not defined herein may be defined in the AWS Agreements (as defined below). You and/or the Principal Investigator are responsible for distributing these Rules to all members of the research team before they participate in any research in connection with a proposal funded by the ARA Program.

I. Eligibility Requirements

To be eligible for an ARA Program award (“Award”), the Principal Investigator must be (1) either a full-time faculty member at an accredited academic institution or a permanent researcher at a non-governmental organization with recognized legal status in its country (equivalent to 501(c)(3) status under the United States Internal Revenue Code) and (2) at or above the age of majority in their jurisdiction of residence at the time of application. Each Principal Investigator is permitted to submit only one proposal to the ARA Program per call for proposal period.

By submitting your proposal to the ARA Program, you represent that your Principal Investigator:

(a) is not a paid employee of a government entity (other than an accredited academic institution);

(b) is not under US export controls or sanctions;

(c) has not been a director, officer, employee, intern or contractor of Amazon within the 12 months preceding submission of your proposal to the ARA Program (“Ineligible Personnel”);

(d) is not a member of the immediate family or household of Ineligible Personnel; and

(e) has not participated in or had decision-making authority over any cloud infrastructure procurements involving Amazon.

The ARA Program is void in Cuba, Iran, Syria, North Korea and the Crimea, Luhansk and Donetsk regions of Ukraine, and where otherwise prohibited by law.

Amazon employees, including employees of Amazon Web Services, Inc. (“AWS”), are not eligible to receive an Award.

Amazon is not responsible for your internal organizational policies and procedures that may restrict your (including the Principal Investigator’s) ability to submit a proposal to the ARA Program.

II. Application Content

No proposal to the ARA Program may contain any confidential information and no part may be marked as ‘confidential.’ Amazon does not accept any legal obligation (whether of confidentiality, compensation, return or otherwise) with respect to any proposals. Amazon reserves the right to implement competitive, similar, or identical ideas in the future, without restriction or obligation. You understand and acknowledge that Amazon has wide access to technology, designs, and other materials, and may work on and/or develop projects and ideas that may be competitive with, similar to, or identical to your proposal in theme, idea, format or other respects, inclusive. You acknowledge and agree that you will not be entitled to any compensation as a result of Amazon’s use of any such similar or identical material that has or may come to Amazon from other sources.

You represent and warrant that your proposal:

(a) is either your original work or an update to your original work;

(b) does not, to your knowledge, infringe any third-party patent rights; and

(c) does not, to your knowledge, infringe, misappropriate or otherwise violate any other third-party intellectual property rights (i.e., other than patent rights), including any copyrights, trade secrets, trademarks, contract or licensing rights, rights of publicity or privacy, or moral rights.

III. Awards

Proposals selected for funding will receive an Award that may include cash, Promotional Credit (as defined in the AWS Promotional Credit Terms & Conditions), or both. Award funding is not extendable or transferable without our written consent, but you may submit new proposals for subsequent ARA Program calls.

All Award amounts will be determined by Amazon in its sole discretion. Any cash component of an Award:

(a) will be structured as a one-time unrestricted gift to your Principal Investigator’s academic institution or organization;

(b) will be provided directly to your academic institution or organization for distribution and management; and

(c) may not be used for indirect expenses which are not allocable, reasonable, adequately documented, and consistent with established policies and practices of your academic institution or organization.

You are responsible for the administration and apportionment of any costs and expenses associated with an Award, including any allowable and allocable overhead or indirect costs. In order to process any cash Award, you will be required to complete administrative requirements, which may include submitting a W-9 form to us, completing a tax questionnaire, and registering in Amazon’s Payee Central System. If you do not fulfill the administrative requirements for processing cash Awards within two years of your receipt of an Award notification, Amazon reserves the right to withhold payment. Any payment from Amazon to you under the Award may be issued by a purchase order. Except where prohibited by law, you are responsible for all taxes (including income tax and value added tax) that may be imposed on you by relevant local tax authorities.

These Rules, the agreements referenced herein, and any other agreement regarding the relationship between you and Amazon will constitute a Master Agreement under the terms of the purchase order.

IV. AWS Customer Agreement and AWS Promotional Credit Terms & Conditions

Amazon may make available to you an amount of AWS promotional computing credits (“AWS Credits”) for use in support of this Agreement. AWS Credits provided to University under this Agreement are subject to the AWS Promotional Credit Terms and Conditions (as may be updated from time to time on the AWS website). You acknowledge and agree that any use of AWS services, including but not limited to use of AWS Credits, is subject to the terms and conditions set forth in the AWS Customer Agreement (https://aws.amazon.com/agreement/), and/or any separate, bespoke agreement that you have entered into with Amazon governing use of AWS services (collectively, the “AWS Agreements”). In the event of any conflict between this Agreement and the AWS Agreements, the terms of the AWS Agreements shall take precedence.

V. Privacy

You acknowledge and agree that we may collect, store, share, and otherwise use personally identifiable information provided during the ARA Program application process, including but not limited to, name, mailing address, phone number, and email address. All personally identifiable information collected is subject to, and will be used in accordance with, the Amazon Privacy Notice, including for administering the ARA Program and verifying applicants’ identities, addresses, and telephone numbers in the event a proposal is selected for funding. By participating in the ARA Program, you consent to the transfer of personal data to the United States for purposes of administering the ARA Program, conducting publicity about the ARA Program, and additional purposes that are consistent with goals relating to the ARA Program. The data controller for information collected by us is Amazon.com, Inc., 410 Terry Ave North, Seattle, Washington 98109, USA.

VI. Publicity

Except where prohibited, you consent to our use of your name and the Principal Investigator’s name and title, proposal title, and proposal abstract text for purposes of identifying Amazon’s support of you, the Principal Investigator, the proposal and/or the ARA Program.

You may acknowledge our support by stating that your research is supported by the ARA Program (e.g., “Research reported in this [publication/press release] was supported by an Amazon Research Award, [Cycle /Year].”). Any use of Amazon or AWS logos is subject to the Amazon Trademark Guidelines and AWS Trademark Guidelines, respectively. Any other use of Amazon or AWS logos requires Amazon’s or such affiliate’s prior written consent. You must receive Amazon’s prior written consent before issuing a press release or making any public disclosure regarding your participation in the ARA Program. You agree not to misrepresent or embellish the relationship between us and you. You will not imply any relationship or affiliation between us and you except as expressly permitted by these Rules.

VII. Limitation of Liability

TO THE EXTENT PERMITTED BY APPLICABLE LAW, YOU ACCEPT THE CONDITIONS STATED IN THESE RULES, AGREE TO BE BOUND BY THE DECISIONS OF AMAZON, AND WARRANT THAT YOU ARE ELIGIBLE TO PARTICIPATE IN THE ARA PROGRAM. TO THE EXTENT PERMITTED BY APPLICABLE LAW, YOU, EACH RESEARCH TEAM MEMBER, THE PRINCIPAL INVESTIGATOR AND THE PRINCIPAL INVESTIGATOR’S INSTITUTION HEREBY RELEASES AMAZON FROM, AND WAIVES ANY AND ALL CLAIMS AGAINST AMAZON FOR, ANY LOSSES, LIABILITY, AND DAMAGES OF ANY KIND, (INCLUDING FOR ANY LOSS OF DATA, LOST PROFITS, COST OF COVER OR OTHER SPECIAL, INCIDENTAL, CONSEQUENTIAL, INDIRECT, PUNITIVE, EXEMPLARY OR RELIANCE DAMAGES) INCURRED OR SUSTAINED IN CONNECTION WITH OR ARISING OUT OF (1) THE ARA PROGRAM OR ANY TRAVEL OR ACTIVITY RELATED THERETO, (2) USE OF ANY PROPOSAL OR RIGHTS THEREIN, OR (3) ANY BREACH OF ANY AGREEMENT OR WARRANTY ASSOCIATED WITH THE ARA PROGRAM, INCLUDING THESE RULES, HOWEVER CAUSED AND REGARDLESS OF THEORY OF LIABILITY.

VIII. Changes

We may amend any of these Rules at our sole discretion by posting the revised terms on the ARA Program website. Your continued participation in the ARA Program after the effective date of the revised Rules constitutes your acceptance of the rules.

IX. Disputes

Any dispute or claim relating in any way to the ARA Program will be resolved in accordance with terms set forth in the AWS Agreements.

X. Representations and Warranties

You represent and warrant that:

(a) your receipt of any Award is neither prohibited by nor inconsistent with any applicable laws, regulations, or binding orders, including applicable ethics rules or internal institutional rules;

(b) you have completed or will complete all legal and ethical requirements necessary to accept the Award;

(c) your receipt of the Award will not knowingly create a conflict of interest for Amazon;

(d) the Principal Investigator has not participated in, nor had, and do not anticipate participating in or having, any decision-making authority over, any procurements or purchasing decisions involving Amazon on behalf of your organization during the previous or upcoming twelve (12) months; and

(e) you will properly book and record the Award in your accounting documents in accordance with applicable laws and regulations.

In the event that your representations and warranties under this section are or become inaccurate, you must notify us immediately (research-awards@amazon.com) and any Award your organization receives will be voidable.

IN, KA, Bengaluru
Alexa+ is the world’s best Generative AI powered personal assistant / agent for consumers, and is becoming the conversational AI interface for Amazon services with the launch of Alexa for Shopping on Amazon.com and Amazon mobile app. At Alexa Ads, we are creating industry's first and most advanced Agentic Advertising products to drive Agentic Commerce. We are seeking an Applied Scientist to join our newly expanding team in India focused on Alexa Agentic/Conversational Ads and Personalization. In this role, you will build machine learning models that seamlessly and naturally integrate relevant advertising into the Alexa experience while deeply personalizing user interactions. You will work closely with other scientists, engineers, and product managers to take models from conception to production. Key job responsibilities - Design, develop, and evaluate innovative machine learning and deep learning models for natural language processing (NLP), recommendation systems, and personalization. - Conduct hands-on data analysis and build scalable ML pipelines. - Design and run A/B experiments to measure the impact of new models on customer experience and ad performance. - Collaborate with software development engineers to deploy models into high-scale, real-time production environments. About the team We are building a new science team in Bangalore to solve some of the most impactful problems in computational advertising. This isn't about tweaking existing models as we are rethinking how ads are ranked, priced, and personalized across voice-first and screen-first surfaces. These are problems that don't have textbook solutions. Key points to note about the team: 🧪 Greenfield team - you are not joining a mature org with rigid processes. You will shape the science roadmap, pick the problems, and define the culture from day one. 📈 Direct business impact — your models directly drive revenue. No yearly cycles to see if your work matters. 🌏 Global scope, local autonomy — collaborate with scientists and engineers across Seattle, Sunnyvale, and Bangalore, but own your problem space end-to-end. 🎓 Ship AND Publish: We encourage top-tier publications (NeurIPS, ACL, EMNLP, KDD, ICML, WWW) while ensuring your research hits production.
US, CA, Palo Alto
Are you passionate about solving big problems from ground-up? Do you enjoy building new state-of-the-art products at internet scale? Come lead the innovation in this startup team, vertical ad products. This is a green field problem without a known answer or a pattern to follow. We have ambitious vision to simplify full funnel advertising solutions, at scale, with specialized agentic AI-powered models and diversify the demand to strategic verticals including finserv, autos, locals.. etc. We are seeking an experienced Sr Data Scientist to drive innovation in our Ads Foundational Model. In this individual contributor role, you will apply advanced machine learning techniques to improve advertiser performance and customer experience. Key job responsibilities As a Data Scientist on this team, you will: 1. Develop and drive the science strategy for Ads Foundational Model (Ads-FM), aligning it with the program's objectives and overall business goals. 2. Identify high-impact opportunities within Ads-FM program and lead the ideation, planning, and execution of science initiatives to address them. 3. Build and deploy machine learning models using computer vision, natural language processing, and deep learning to evaluate and enhance ad effectiveness. 4. Develop algorithms that extract meaningful signals from image, video, and audio content to predict and improve customer engagement 5. Leverage Amazon's extensive data repository to create predictive models that generate actionable recommendations for more compelling ad creative 6. Collaborate with business leaders and cross-functional teams to implement ML-powered solutions 7. Contribute to the ML roadmap for the Ads-FM program through innovation and research.
IN, TS, Hyderabad
Are you passionate about solving complex problems with machine learning and scientific rigor? As an Applied Scientist I at Amazon, you will translate real-world business challenges into well-defined scientific problems and build solutions that directly benefit customers. You will work alongside experienced scientists and engineers, applying your expertise in areas such as natural language processing, computer vision, or robotics to design experiments, develop models, and deliver production-ready code. This is a role where your curiosity and technical depth will drive meaningful impact from day one. Key job responsibilities - Design, develop, and implement machine learning models and algorithms to solve well-defined business problems, mapping business goals and metrics to scientific approaches and evaluation criteria. - Write secure, stable, testable, and maintainable production code, applying state-of-the-art data structures and algorithms while following software development best practices at a high quality bar. - Conduct rigorous experiments to evaluate model performance, benchmark results against current research, and iterate on solutions to improve accuracy and customer outcomes. - Collaborate with team members to scope technical approaches, communicate findings through internal research reports, and contribute to peer-reviewed publications when aligned with business needs. - Stay current with research trends in your area of expertise, champion the adoption of recent scientific advancements, and help onboard and mentor scientist interns. A day in the life You might start your morning reviewing experiment results from a model you trained, analyzing performance metrics and identifying areas for improvement. After a design discussion with your team, you refine your approach and push updated code for review. In the afternoon, you read a recent research paper recommended by a senior scientist, exploring whether a new technique could improve your current solution. You wrap up by documenting your methodology so teammates can understand and build on your work. About the team Our team is focused on applying scientific methods and machine learning to solve problems that matter to Amazon's customers. We value rigorous experimentation, clear communication, and a collaborative environment where scientists at every stage of their career can grow. We are building toward solutions that push the boundaries of what is possible, and we are looking for curious, thoughtful scientists who want to contribute to that mission and learn alongside a supportive group of peers.
IN, TS, Hyderabad
Welcome to the Worldwide Returns & ReCommerce team (WWR&R) at Amazon.com. WWR&R is an agile, innovative organization dedicated to ‘making zero happen’ to benefit our customers, our company, and the environment. Our goal is to achieve the three zeroes: zero cost of returns, zero waste, and zero defects. We do this by developing products and driving truly innovative operational excellence to help customers keep what they buy, recover returned and damaged product value, keep thousands of tons of waste from landfills, and create the best customer returns experience in the world. We have an eye to the future – we create long-term value at Amazon by focusing not just on the bottom line, but on the planet. We are building the most sustainable re-use channel we can by driving multiple aspects of the Circular Economy for Amazon – Returns & ReCommerce. Amazon WWR&R is comprised of business, product, operational, program, software engineering and data teams that manage the life of a returned or damaged product from a customer to the warehouse and on to its next best use. Our work is broad and deep: we train machine learning models to automate routing and find signals to optimize re-use; we invent new channels to give products a second life; we develop highly respected product support to help customers love what they buy; we pilot smarter product evaluations; we work from the customer backward to find ways to make the return experience remarkably delightful and easy; and we do it all while scrutinizing our business with laser focus. You will help create everything from customer-facing and vendor-facing websites to the internal software and tools behind the reverse-logistics process. You can develop scalable, high-availability solutions to solve complex and broad business problems. We are a group that has fun at work while driving incredible customer, business, and environmental impact. We are backed by a strong leadership group dedicated to operational excellence that empowers a reasonable work-life balance. As an established, experienced team, we offer the scope and support needed for substantial career growth. Amazon is earth’s most customer-centric company and through WWR&R, the earth is our customer too. Come join us and innovate with the Amazon Worldwide Returns & ReCommerce team! Key job responsibilities * Design, develop, and evaluate highly innovative models for Natural Language Programming (NLP), Large Language Model (LLM), or Large Computer Vision Models. * Use SQL to query and analyze the data. * Use Python, Jupyter notebook, and Pytorch to train/test/deploy ML models. * Use machine learning and analytical techniques to create scalable solutions for business problems. * Research and implement novel machine learning and statistical approaches. * Mentor interns. * Work closely with data & software engineering teams to build model implementations and integrate successful models and algorithms in production systems at very large scale. About the team When a customer returns a package to Amazon, the request and package will be passed through our WWRR machine learning (ML) systems so that we could improve the customer experience, identify return root cause, optimize re-use, and evaluate the returned package. Our problems touch multiple modalities spanning from: textual, categorical, image, to speech data. We operate at large scale and rely on state-of-the-art modeling techniques to power our ML models: XGBoost, BERT, Vision Transformers, Large Language Models.
US, TX, Austin
Amazon Leo is an initiative to launch a constellation of Low Earth Orbit satellites providing low-latency, high-speed broadband connectivity to unserved and underserved communities around the world. As a Communication Systems Research Scientist, this role owns the research and system design of the radio resource management (RRM) and radio access layers of Amazon Leo’s direct-to-device (D2D) system, delivering 3GPP-compliant service to unmodified commercial handsets. The Role: Be part of the team defining the communication system and architecture of Amazon’s direct-to-device wireless network and analyzing its system level performance: beam and cell capacity, spectral efficiency, coverage, latency and service availability. This is a unique opportunity to innovate with few legacy constraints, in a segment where the standard itself is still being written. This role leads the research and system design of radio resource management (RRM) for a 3GPP Non-Terrestrial Network (NTN), where D2D upends terrestrial assumptions: a power-limited handset with a near-isotropic antenna, very large cells, hopping beams, large time-varying delay and Doppler, and scarce shared spectrum. RRM in time, frequency and spatial domains is the focus, but the role reasons across the stack, from L1/L2 up through RRC, NAS and 5GC interworking. Agentic AI is expected to be a standard part of the work for development, optimization, tests and debugging, with the scientist accountable for the algorithms, models and conclusions. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum. Key job responsibilities • Research, design and specify RRM algorithms for Amazon Leo’s 3GPP-based D2D system: MAC scheduling, link adaptation, power control, HARQ strategy, DRX, admission and congestion control, and load balancing, mapping 5QI and QoS flow requirements to scheduler behavior across voice, messaging, emergency and data services. • Treat beam management as part of joint resource optimization, not a standalone process, optimizing it with band assignment, packet scheduling and user pairing in multi-user MIMO (MU-MIMO). • Define the RRM framework for NTN conditions: earth-fixed and earth-moving cells, large time-varying propagation delay, ephemeris-assisted timing and Doppler pre-compensation, extended timing advance, selective HARQ feedback disabling, feeder link and satellite handovers, and interference and spectrum sharing across beams, satellites and terrestrial networks using the same MNO spectrum. • Design mobility and service continuity for a network where the base stations (i.e., satellites) move rather than the user: idle and connected mode mobility, location and time based conditional handover, cell reselection, paging, tracking area design, and NTN-to-terrestrial continuity. • Specify supporting L1/L2 elements with the PHY team: numerology under Doppler, PRACH and initial access, coverage enhancement through repetition, synchronization at low SNR, receiver abstraction, and FEC and BLER modeling for link adaptation. • Keep the radio design coherent with the networking layers: RRC and NAS, RLC and PDCP over long-RTT links, CU/DU split, NTN gateway and 5GC/EPC integration, and transport behavior. • Develop link-level and system-level simulators capturing constellation dynamics, beam patterns, handset characteristics, traffic models and RRM behavior, and use agentic AI across that loop: build and refactor simulation code, scale parameter sweeps, optimize scheduler and link adaptation parameters, explore configuration spaces too large to sweep by hand, maintain regression tests, and triage failures across logs, traces and over-the-air captures. • Translate research into system requirements and implementation-level specifications, and work with modem, payload, ground, RF, ASIC and Testbed teams through integration, field trials and link bring-up, root-causing gaps between simulation, implementation and over-the-air behavior in a fast-paced environment. • Represent Amazon Leo in 3GPP and other standards development organizations, develop and defend contributions on NTN and D2D work items, and contribute patents and publications.
US, CA, San Diego
Amazon Leo is an initiative to launch a constellation of Low Earth Orbit satellites that will provide low-latency, high-speed broadband connectivity to unserved and underserved communities around the world. Come work at Amazon! The Role: Be part of the team defining the overall communication system and architecture of Leo’s broadband wireless network. This is a unique opportunity to innovate and define groundbreaking wireless technology with few legacy constraints. The team develops and designs the communication system of Leo and analyzes its overall system level performance such as for overall throughput, latency, system availability, packet loss etc. This role in particular will be responsible for leading the effort in integration, verification and testing of the systems especially focused on MAC and higher layer testing. This role will also be responsible developing and testing advanced L1/L2/L3 concept to improve the performance and reliability of the LEO network. This role will also be part of a team and develop simulation tools with particular emphasis on modeling the physical layer aspects such as advanced receiver modeling and abstraction, interference cancellation techniques, FEC abstraction models etc. In this role you will: - Work within a project team and take the responsibility for the Leo’s communication system design, system integration and verification. - Work as a part of the team in building a suite of system and network simulation services in Matlab / C++ / Python - Develop requirements from system level to HW/SW level and define test cases associated with the requirements. - Identify additional HW and SW that are needed for the purposes of verification and guide the HW/SW development team in the development of these test solutions/tools// - Work closely with implementation teams to simulate expected system level performance and provide quick feedback on potential improvements - Write scripts / code for functions / features required for specific simulation, testing and verification of given RF system EXPORT CONTROL REQUIREMENTS Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.
US, WA, Seattle
Amazon Economics is seeking Structural IO Economist (STRUC) Interns who are passionate about applying structural econometric methods to solve real-world business challenges. STRUC economists specialize in the econometric analysis of models that involve the estimation of fundamental preferences and strategic effects. In this full-time internship (40 hours per week, with hourly compensation), you'll work with large-scale datasets to model strategic decision-making and inform business optimization, gaining hands-on experience that's directly applicable to dissertation writing and future career placement. By applying to this role, you are automatically being considered for all our available STRUC internships in 2027. Key job responsibilities As a STRUC Economist Intern, you'll specialize in structural econometric analysis to estimate fundamental preferences and strategic effects in complex business environments. Your responsibilities include: - Analyze large-scale datasets using structural econometric techniques to solve complex business challenges - Applying discrete choice models and methods, including logistic regression family models (such as BLP, nested logit) and models with alternative distributional assumptions - Utilizing advanced structural methods including dynamic models of customer or firm decisions over time, applied game theory (entry and exit of firms), auction models, and labor market models - Building datasets and performing data analysis at scale - Collaborating with economists, scientists, and business leaders to develop data-driven insights and strategic recommendations - Tackling diverse challenges including pricing analysis, competition modeling, strategic behavior estimation, contract design, and marketing strategy optimization - Helping business partners formalize and estimate business objectives to drive optimal decision-making and customer value - Build and refine comprehensive datasets for in-depth structural economic analysis - Present complex analytical findings to business leaders and stakeholders
US, VA, Arlington
Want to help Amazon tell its customer-centric story around the world and work in a highly cross-functional environment with economists, lawyers, scientists, public policy, public relations, and business teams? If yes, keep reading! You'll join a team of economists, engineers, and lawyers to develop economic analysis and evidence supporting legal and regulatory matters across all our lines of business worldwide—including retail, marketplace services, AWS, consumer experience, shopping and search, and operations. In this role, you will have exposure to complex regulatory issues that are of high strategic importance to the company and will develop significant expertise on the economics of Amazon’s business operations and the industries in which it operates. If you're an economist with a passion for the current legal and policy debate, strong practical judgment and creative problem-solving skills, a love of communicating economic ideas to non-technical audiences, a knack for distilling data and economic models into key insights, and a track record of delivering results fast, we want to talk to you! Key job responsibilities • Provide data-driven guidance on high-stakes legal and regulatory questions facing Amazon worldwide • Collaborate with economists, scientists, engineers, and non-technical partners on high-impact projects with global scope • Partner with global public policy teams to apply economic analyses to current policy debates on competition, AI, and related issues • Engage with external stakeholders to drive deeper understanding of Amazon’s business model and the value it develops for the economy • Support requests for economic analyses and data in ongoing regulatory and litigation matters worldwide • Synthesize business facts and data into compelling economic narratives, translating complex findings into actionable insights • Advise stakeholders across Amazon on a broad spectrum of complex and often novel economic issues • Conduct, direct, and coordinate all phases of research projects—defining key questions, evaluating methodology, executing analysis, and communicating results
US, WA, Seattle
Amazon Economics is seeking Reduced Form Causal Analysis (RFCA) Economist Interns who are passionate about applying econometric methods to solve real-world business challenges. RFCA represents the largest group of economists at Amazon, and these core econometric methods are fundamental to economic analysis across the company. In this a full-time internship (40 hours per week, with hourly compensation). You'll work with large-scale datasets to analyze causal relationships and inform strategic business decisions, gaining hands-on experience that's directly applicable to dissertation writing and future career placement. By applying to this role, you are automatically being considered for all our available RFCA internships in 2027. Key job responsibilities As an RFCA Economist Intern, you'll specialize in econometric analysis to determine causal relationships in complex business environments. Your responsibilities include: - Analyze large-scale datasets using advanced econometric techniques to solve complex business challenges - Applying econometric techniques such as regression analysis, binary variable models, cross-section and panel data analysis, instrumental variables, and treatment effects estimation - Utilizing advanced methods including differences-in-differences, propensity score matching, synthetic controls, and experimental design - Building datasets and performing data analysis at scale - Collaborating with economists, scientists, and business leaders to develop data-driven insights and strategic recommendations - Tackling diverse challenges including program evaluation, elasticity estimation, customer behavior analysis, and predictive modeling that accounts for seasonality and time trends - Build and refine comprehensive datasets for in-depth economic analysis - Present complex analytical findings to business leaders and stakeholders
US, WA, Bellevue
FBA AI Science and Analytics accelerates the AI-native transformation of Fulfillment by Amazon by building, integrating, and scaling AI-powered data & science products and seller-facing experiences that drive operational efficiency and growth across Fulfillment by Amazon globally. We learn seller behaviors, design the policies and incentives that shape their experience, and ship science products that help third-party sellers grow topline and cut operating costs at Amazon scale. Our work sits at the intersection of machine learning, statistics, economics, operations research, and GenAI/LLMs. We're looking for a Senior Applied Scientist who wants to put GenAI to work on a hard, high-visibility problem: building next-generation multi-agent systems that interact with millions of sellers and guide them through their toughest challenges at scale. You'll own solutions spanning supervised and unsupervised learning, recommendation systems, statistical learning, LLMs, harness engineering, and reinforcement learning. The ambition is to make AI a native layer in every seller decision rather than a separate tool sellers must adopt, delivering actionable insight in minutes, not days. You'll shape end-to-end experiences across the highest-frequency seller workflows, including inventory optimization, inbound efficiency, defect improvements, reimbursements, and capacity planning. The role carries direct visibility with senior Amazon business leaders and works together with fellow scientists, engineers, and product teams to launch production-grade agentic capabilities. Key job responsibilities - Design, build and deploy FBA’s GenAI architectures end to end. - Apply state-of-the-art ML and GenAI solve diverse business problems across seller supply chain systems. - Define the team’s long-term science vision and roadmap, driven fundamentally from our customers' needs, translating those directions into specific plans for scientists, engineers, and product partners. - Partner closely with scientists and software engineers to drive real-time model implementations and deliver high-impact features. - Establish scalable, efficient, automated processes for large scale data analyses, model benchmarking, model evaluation and model implementation. - Advocate the right ML solutions to business stakeholders, engineering teams, as well as executive level decision makers