Careers

The Seller External Relations (SER) team ensures that Amazon is viewed globally by external audiences as a valuable, accessible, partner who respects and celebrates the success of its sellers. We develop strategic, data-supported, messaging and publish external reports that demonstrate and celebrate the positive experiences of sellers on Amazon to other sellers, the general public, and influentials (e.g., media and policymakers) with the goal of improving their perception of the experience and benefits of selling in our store. As Sr. Economist for SER, you will build the science models and the supporting structures needed to analyze, dive deep, and develop underlying data for our external messaging and reports. Your work will demonstrate how Amazon’s innovation enables seller success and supports their growth. You will have the opportunity to present findings to cross functional team partners to drive improvements. You will work closely with other Applied/Research/Data Scientists, Economists, Data Engineers, Software Development Engineers, Program Managers and Business Partners to solve challenging problems. You need be comfortable using intellect, curiosity and technical ability to develop innovative solutions to business problems. You will become an expert on aspects of the business to understand how to apply science and analytics to develop and substantiate our strategic messaging. You'll thrive if you enjoy tackling ambiguous challenges using the economics toolkit to identify and solve problems at scale. You will be expected to provide clear and concise explanation of results and approaches, provide opinion and guidance on problem solving, and present to senior leadership across multiple business units. The ideal candidate will have outstanding leadership skills, proven ability to develop, enhance, automate, and manage science models from end to end. The ideal candidate will have strong data mining and modeling skills and will be comfortable facilitating idea creation and working from concept through to execution. The ideal candidate must have demonstrated ability to manage medium-scale automation and modeling projects, identify requirements and build methodology and tools that are mathematically grounded but also explainable operationally, apply technical skills allowing the models to adapt to changing attributes. Key job responsibilities • Contribute to external messaging and report strategy based on science models and data analysis • Develop models to measure long term impact of the relationship between Amazon selling tools and seller behavior • Collaborate with product and engineering teams across the business to develop comprehensive models with diverse inputs • Use economical techniques to discover and develop underlying data for our strategic messaging and report work • Research, experiment and implement novel approaches. • Work closely with other scientists across teams. • Use the best practices in science: data integrity, design, test, and implementation and documentation. About the team SER is functionally diverse organization that includes a broad spectrum of skillsets and job families. We are a team of program and product managers, business analysts, creatives, storytellers, and small business evangelists - all important contributors to our work in ensuring that perception of Amazon’s support of small business matches reality. We have a supportive, fast-paced team culture, and we prioritize learning, growth, and helping each other to continuously raise the bar. Your direct team would be comprised of product and program managers, business analysts, and data engineers, with stakeholders and partners in similar functions accross the organization.

Amazon's Search Science and AI team creates ML algorithms that connect customers around the world with products that delight them. We harness cutting-edge ML at Amazon's scale to make the customer experience easier and smoother. Our impact is large. For example, if your innovations save even 1 minute per customer per year, then for every 100 million customers, you save approximately 190 years of human effort. Key job responsibilities You will build search ranking systems that work for thousands of product types, billions of queries, and hundreds of millions of customers spread around the world. As an Applied Scientist you will find the next set of big improvements to ranking, leverage large datasets to understand the complexities of customer behavior, and get your hands dirty by building ML models that work at Amazon scale. In addition to typical topics in ranking, we are particularly interested in exploration techniques and reinforcement learning. A day in the life Our primary focus is improving search ranking systems. On a day-to-day this means building ML models, analyzing data from your recent A/B tests, and guiding teams on best practices. You will also find yourself in meetings with business and tech leaders at Amazon communicating your next big initiative. About the team We are a team consisting of ML scientists and software engineers. Our interests and activities span machine learning for better ranking, statistics for better decision making, and infrastructure to make it all happen at scale and efficiently.

Are you excited about delighting millions of customers by driving the most relevant marketing initiatives? Do you thrive in a fast-moving, large-scale environment that values data-driven decision making and sound scientific practices? Amazon is seeking a Data Scientist . This team is focused on driving key priorities of a)core shopping that elevates the shopping CX for all shoppers in all lifecycle stages, b) developing ways to accelerate lifecycle progression and build foundational capabilities to address the shopper needs and c)Alternate shopping models We are looking for a Data Scientist to join our efforts to support the next generation of analytics systems for measuring consumer behavior using machine learning and econometrics at big data scale at Amazon. You will work machine learning and statistical algorithms across multiple platforms to harness enormous volumes of online data at scale to define customer facing products and measure customer responses to various marketing initiatives. The Data Scientist will be a technical player in a team working to build custom science solutions to drive new customers, engage existing customers and drive marketing efficiencies by leveraging approaches that optimize Amazon’s systems using cutting edge quantitative techniques. The right candidate needs to be fluid in: · Data warehousing and EMR (Hive, Pig, R, Python). · Feature extraction, feature engineering and feature selection. · Machine learning, causal inference, statistical algorithms and recommenders. · Model evaluation, validation and deployment. · Experimental design and testing.

Join us at Amazon as we reinvent shopping again! We're not just talking about improving the existing Amazon shopping experiences, we're building a brand-new world where shopping is effortless and intuitive through the power of generative AI. Leveraging state-of-the-art Large Language Models and generative AI, we're creating a live, two-way natural language conversational experience that is fast, helpful and trustworthy. As people turn to Amazon for deeper insights and understanding about products earlier and earlier in their shopping journeys, we're stepping up to the challenge by synthesizing complex information and multiple perspectives so customers can explore Amazon’s vast catalog to find exactly the products that solve their particular needs. Imagine having a back and forth conversation with an AI assistant helping you to articulate a problem you’re trying solve, effortlessly answering your product questions and giving you trustworthy advice and recommendations for what to buy. Also imagine a world where this same AI assistant reduces your mental load by proactively predicting and then fulfilling your shopping needs without you needing to interfere, thus saving you time and money along the way. We are building such an AI assistant to become the digital manifestation of the helpful salesperson that asks customers what they need, helps them navigate the store, waits unobtrusively while they look over the shelves, and helps them find complementary goods. What does economics have to teach this salesperson? Can we embed lessons from the behavioral literature to help customers? This is an opportunity to embed economic expertise into large scale generative models. This is just the beginning, and the future is yours to shape. We're searching for pioneers who are passionate about using technology and innovation to fundamentally change how customers shop, and who are ready to make a lasting impact on the industry and even disrupting how Amazon serves customers. You'll be a senior technical leader working with talented scientists, economists, engineers, and product leaders to innovate on behalf of our customers and help turn generative AI shopping into Amazon’s next business pillar. Key job responsibilities As the Principal Economist in the Shopping Economics team, you are a senior member of the technical leadership team, working with executives, principal engineers and scietists, and senior product leaders. Your economic thought leadership helps us to build new-to-world customer experiences that solve important problems for customers while creating new business models, ensuring Amazon is optimizing its innovation portfolio to maximally help customers solve their shopping problems. Solving problems like improving the match quality between customers’ heterogeneous needs and Amazon’s nearly infinite selection, articulating the economics of advertising in a conversation, using insights from economics to better align the LLM, and using deep learning techniques to measure substitution patterns and the economic value of engagement. You work with economists, scientists, and engineers Amazon-wide to rethink systems across the company to better optimize for helping customers through their entire shopping journey. You also develop and evangelize new mental models and new ways to measure the economic value of bleeding edge generative AI. As the senior economist in the team, you also guide the work and careers of other economists on the team.

AMZL Global Fleet and Products (GFP) organization is responsible for fleet programs and capacity for Last Mile deliveries. The Fleet Planning team is looking for a Data Scientist to drive the most efficient use of fleet. Last Mile fleet planning is a complex resource allocation problem. The goal of fleet allocation planning is to optimize the size and mix of fleet allocated to DSPs through various programs to improve branded fleet utilization. Changes in routes, last mile network, exiting DSPs and new DSP onboarding create continuous need for re-allocation of fleet to maintain an efficient network capacity. This requires allocation to adhere to various operational limits (repair network, EV range, Station Charging capability) and also match route’s cube need to vehicles capacity. As a Data Scientist on the Fleet Planning team (GFP), you will be responsible for building new science models (linear programs, statistical and ML models) and enhancing existing models for changing business needs. You would work with program managers in planning, procurement, redeployment, deployment, remarketing, variable fleet and infrastructure programs to build models that would support the requirements of all programs in a coherent plan. Key job responsibilities • Build models and automation for planners for generating vehicle allocation plans • Partner with program teams to test and measure success of implemented model • Lead reviews with senior leadership, deep dive model outputs and explain implications of model recommendations.

Do you want to join an innovative team of scientists who use deep learning, natural language processing, large language models to help Amazon provide the best seller experience across the entire Seller life cycle, including recruitment, growth, support and provide the best customer and seller experience by automatically mitigating risk? Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of customer interactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems? Are you excited by the opportunity to leverage GenAI and innovate on top of the state-of-the-art large language models to improve customer and seller experience? Do you like to build end-to-end business solutions and directly impact the profitability of the company? Do you like to innovate and simplify processes? If yes, then you may be a great fit to join the Machine Learning Accelerator team in the Amazon Selling Partner Services (SPS) group. Key job responsibilities The scope of an Applied Scientist III in the Selling Partner Services (SPS) Machine Learning Accelerator (MLA) team is to research and prototype Machine Learning applications that solve strategic business problems across SPS domains. Additionally, the scientist collaborates with engineers and business partners to design and implement solutions at scale when they are determined to be of broad benefit to SPS organizations. They develop large-scale solutions for high impact projects, introduce tools and other techniques that can be used to solve problems from various perspectives, and show depth and competence in more than one area. They influence the team’s technical strategy by making insightful contributions to the team’s priorities, approach and planning. They develop and introduce tools and practices that streamline the work of the team, and they mentor junior team members and participate in hiring.

Are you inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Robotics. We are a smart team of doers who work passionately to apply cutting edge advances in robotics and software to solve real-world challenges that will transform our customers’ experiences. We invent new improvements every day. We are Amazon Robotics and we will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling, and fun. Amazon Robotics is seeking students to join us for a 5-6 month internship (full-time, 40 hours per week) as Data Science Co-op. Please note that by applying to this role you would be considered for Data Scientist spring co-op and fall co-op roles on various Amazon Robotics teams. The internship/co-op project(s) and location are determined by the team the student will be working on. Learn more about Amazon Robotics: https://amazon.jobs/en/teams/amazon-robotics About the team Amazon empowers a smarter, faster, more consistent customer experience through automation. Amazon Robotics automates fulfillment center operations using various methods of robotic technology including autonomous mobile robots, sophisticated control software, language perception, power management, computer vision, depth sensing, machine learning, object recognition, and semantic understanding of commands. Amazon Robotics has a dedicated focus on research and development to continuously explore new opportunities to extend its product lines into new areas.

The Learning & Development Science team in Amazon Logistics (AMZL) builds state-of-the-art Artificial Intelligence (AI) solutions for enhancing leadership and associate development within the organization. We develop technology and mechanisms to map the learner journeys, answer real-time questions through chat assistants, and drive the right interventions at the right time. As an Applied Scientist on the team, you will play a critical role in driving the design, research, and development of these science initiatives. The ideal candidate will lead the research on learning and development trends, and develop impactful learning journey roadmap that align with organizational goals and priorities. By parsing the information of different learning courses, they will utilize the latest advances in Gen AI technology to address the personalized questions in real-time from the leadership and associates through chat assistants. Post the learning interventions, the candidate will apply causal inference or A/B experimentation frameworks to assess the associated impact of these learning programs on associate performance. As a part of this role, this candidate will collaborate with a large team of experts in the field and move the state of learning experience research forward. They should have the ability to communicate the science insights effectively to both technical and non-technical audiences. Key job responsibilities * Apply science models to extract actionable information from learning feedback * Leverage GenAI/Large Language Model (LLM) technology for scaling and automating learning experience workflows * Design and implement metrics to evaluate the effectiveness of AI models * Present deep dives and analysis to both technical and non-technical stakeholders, ensuring clarity and understanding and influencing business partners * Perform statistical analysis and statistical tests including hypothesis testing and A/B testing * Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation

Lead the development of cutting-edge AI models to power Amazon's eCommerce ontology - the authoritative source of product knowledge driving exceptional customer experiences. Applied Scientists in this role solve problems related to product classification, attribute extraction, ontology modeling, data integration and enrichment, and scalable knowledge services. It's challenging due to the vast scale, heterogeneous data sources, and evolving domains, but exciting for pushing boundaries in ML, NLP, and knowledge representation research. If you're passionate about driving innovation at scale, we want to hear from you! Key job responsibilities - Lead the research and development of novel AI solutions to enrich and curate Amazon's product ontology (Product Knowledge) at scale - Develop scalable data processing pipelines and architectures to ingest, transform, and enrich product data from various sources (seller listings, customer reviews, etc.) - Collaborate with engineers to design and implement robust services - Work closely with product managers, stakeholders, and subject matter experts to identify opportunities for innovation and drive the roadmap for Product Knowledge - Mentor and upskill junior scientists and engineers, fostering a culture of continuous learning and knowledge sharing - Communicate complex technical concepts and research findings effectively to diverse audiences, including leadership, cross-functional teams, and the wider scientific community - Stay up-to-date with the latest advancements in machine learning, natural language processing, knowledge representation, and related fields, and identify opportunities to apply them to Product Knowledge A day in the life The Amazon product ontology is a structured knowledge base representing product types, attributes, classes, and relationships. It standardizes product data, enabling enhanced customer experiences through improved search and recommendations, streamlined selling processes, and internal data enrichment across Amazon's eCommerce ecosystem. You will work with following stakeholders: - Product Managers represent customer experiences and selling partner experiences - Category Leaders (e.g., apparel, electronics) provide domain knowledge and guidance as subject matter experts - Engineers build and maintain data pipelines and services in production - Ontologists design data models and define guidelines - Other Applied Scientists collaborate on research and innovation About the team The Product Knowledge team at Amazon is dedicated to creating the industry-standard eCommerce product and services ontology. Our diverse team of applied scientists, engineers, ontologists and subject matter experts build a comprehensive ontology enabling exceptional customer and selling partner experiences through high-quality, contextual product knowledge at scale.

Amazon’s Last Mile Team is looking for a passionate individual with strong optimization and analytical skills to join its Last Mile Science team in the endeavor of designing and improving the most complex planning of delivery network in the world. Last Mile builds global solutions that enable Amazon to attract an elastic supply of drivers, companies, and assets needed to deliver Amazon's and other shippers' volumes at the lowest cost and with the best customer delivery experience. Last Mile Science team owns the core decision models in the space of jurisdiction planning, delivery channel and modes network design, capacity planning for on the road and at delivery stations, routing inputs estimation and optimization. Our research has direct impact on customer experience, driver and station associate experience, Delivery Service Partner (DSP)’s success and the sustainable growth of Amazon. Optimizing the last mile delivery requires deep understanding of transportation, supply chain management, pricing strategies and forecasting. Only through innovative and strategic thinking, we will make the right capital investments in technology, assets and infrastructures that allows for long-term success. Our team members have an opportunity to be on the forefront of supply chain thought leadership by working on some of the most difficult problems in the industry with some of the best product managers, scientists, and software engineers in the industry. Key job responsibilities Candidates will be responsible for developing solutions to better manage and optimize delivery capacity in the last mile network. The successful candidate should have solid research experience in one or more technical areas of Operations Research or Machine Learning. These positions will focus on identifying and analyzing opportunities to improve existing algorithms and also on optimizing the system policies across the management of external delivery service providers and internal planning strategies. They require superior logical thinkers who are able to quickly approach large ambiguous problems, turn high-level business requirements into mathematical models, identify the right solution approach, and contribute to the software development for production systems. To support their proposals, candidates should be able to independently mine and analyze data, and be able to use any necessary programming and statistical analysis software to do so. Successful candidates must thrive in fast-paced environments, which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon's strategic needs. As an applied scientist, you will also help coach/mentor junior scientists in the team.