Customer-obsessed science

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Amazon Science Fulfillment Center OAK4 in Tracy, CA
June 03, 2024
A combination of generative AI and computer vision imaging tunnels is helping Amazon proactively improve the customer experience.

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US, VA, Arlington
The Central Science Team within Amazon’s People Experience and Technology org (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. We are an interdisciplinary team, which combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. We are looking for a Senior Economist who is able to provide structure around complex business problems, hone those complex problems into specific, scientific questions, and test those questions to generate insights. The ideal candidate will work with various science, engineering, operations, and analytics teams 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. They will lead teams of researchers to produce robust, objective research results and insights which can be communicated to a broad audience inside and outside of Amazon. Ideal candidates will work closely with business partners to develop science that solves the most important business challenges. They will work well in a team setting with individuals from diverse disciplines and backgrounds. They will serve as an ambassador for science and a scientific resource for business teams, so that scientific processes permeate throughout the HR organization to the benefit of Amazonians and Amazon. Ideal candidates will own the development of scientific models and manage the data analysis, modeling, and experimentation that is necessary for estimating and validating models. They will be customer-centric – clearly communicating scientific approaches and findings to business leaders, listening to and incorporate their feedback, and delivering successful scientific solutions. We are open to hiring candidates to work out of one of the following locations: Arlington, VA, 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, MA, Boston
The Artificial General Intelligence (AGI) - Automations team is developing AI technologies to automate workflows, processes for browser automation, developers and ops teams. As part of this, we are developing services and inference engine for these automation agents, and techniques for reasoning, planning, and modeling workflows. If you are interested in a startup mode team in Amazon to build the next level of agents then come join us. Scientists in AGI - Automations will develop cutting edge multimodal LLMs to observe, model and derive insights from manual workflows to automate them. You will get to work in a joint scrum with engineers for rapid invention, develop cutting edge automation agent systems, and take them to launch for millions of customers. Key job responsibilities - Build automation agents by developing novel multimodal LLMs. A day in the life An Applied Scientist with the AGI team will support the science solution design, run experiments, research new algorithms, and find new ways of optimizing the customer experience.; while setting examples for the team on good science practice and standards. Besides theoretical analysis and innovation, an Applied Scientist will also work closely with talented engineers and scientists to put algorithms and models into practice. We are open to hiring candidates to work out of one of the following locations: Boston, MA, USA | San Jose, CA, USA
US, CA, San Diego
Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by preventing eCommerce fraud? 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? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you enjoy collaborating in a diverse team environment? If yes, then you may be a great fit to join the Amazon Buyer Risk Prevention (BRP) Machine Learning group. We are looking for a talented scientist who is passionate to build advanced algorithmic systems that help manage safety of millions of transactions every day. Key job responsibilities Use machine learning and statistical techniques to create scalable risk management systems Learning and understanding large amounts of Amazon’s historical business data for specific instances of risk or broader risk trends Design, development and evaluation of highly innovative models for risk management Working closely with software engineering teams to drive real-time model implementations and new feature creations Working closely with operations staff to optimize risk management operations, Establishing scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation Tracking general business activity and providing clear, compelling management reporting on a regular basis Research and implement novel machine learning and statistical approaches We are open to hiring candidates to work out of one of the following locations: San Diego, CA, USA
US, CA, San Diego
Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by preventing eCommerce fraud? 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? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you enjoy collaborating in a diverse team environment? If yes, then you may be a great fit to join the Amazon Buyer Risk Prevention (BRP) Machine Learning group. We are looking for a talented scientist who is passionate to build advanced algorithmic systems that help manage safety of millions of transactions every day. Key job responsibilities Use machine learning and statistical techniques to create scalable risk management systems Learning and understanding large amounts of Amazon’s historical business data for specific instances of risk or broader risk trends Design, development and evaluation of highly innovative models for risk management Working closely with software engineering teams to drive real-time model implementations and new feature creations Working closely with operations staff to optimize risk management operations, Establishing scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation Tracking general business activity and providing clear, compelling management reporting on a regular basis Research and implement novel machine learning and statistical approaches We are open to hiring candidates to work out of one of the following locations: San Diego, CA, USA
US, WA, Seattle
Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by preventing eCommerce fraud? 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? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you enjoy collaborating in a diverse team environment? If yes, then you may be a great fit to join the Amazon Buyer Risk Prevention (BRP) Machine Learning group. We are looking for a talented scientist who is passionate to build advanced algorithmic systems that help manage safety of millions of transactions every day. Key job responsibilities Use machine learning and statistical techniques to create scalable risk management systems Learning and understanding large amounts of Amazon’s historical business data for specific instances of risk or broader risk trends Design, development and evaluation of highly innovative models for risk management Working closely with software engineering teams to drive real-time model implementations and new feature creations Working closely with operations staff to optimize risk management operations, Establishing scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation Tracking general business activity and providing clear, compelling management reporting on a regular basis Research and implement novel machine learning and statistical approaches We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA
US, WA, Bellevue
The Artificial General Intelligence (AGI) team is seeking a dedicated, skilled, and innovative Applied Scientist with a robust background in deep learning, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As part of the AGI team, an Applied Scientist will collaborate closely with talented colleagues to lead the development of advanced approaches and modeling techniques, driving forward the frontier of LLM technology. This includes innovating model-in-the-loop and human-in-the-loop approaches to ensure the collection of high-quality data, safeguarding data privacy and security for LLM training, and more. An Applied Scientist will also have a direct impact on enhancing customer experiences through state-of-the-art products and services that harness the power of speech and language technology. A day in the life An Applied Scientist with the AGI team will support the science solution design, run experiments, research new algorithms, and find new ways of optimizing the customer experience; while setting examples for the team on good science practice and standards. Besides theoretical analysis and innovation, an Applied Scientist will also work closely with talented engineers and scientists to put algorithms and models into practice. The ideal candidate should be passionate about delivering experiences that delight customers and creating robust solutions. They will also create reliable, scalable and high-performance products that require exceptional technical expertise, and a sound understanding of Machine Learning. We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA
US, WA, Seattle
Amazon Worldwide Advertising is one of Amazon's fastest growing and most profitable businesses. Ads Self-serve Products for Experience, Experimentation, and Developer productivity (Ads SPEED) team drives a coherent experience across Amazon Ads Console for all endemic and non-endemic advertisers and their agencies using Amazon’s marketing portfolio to grow their business and brands on and off Amazon. We enable Ad application builders across every product development cycle stage — from decisions to build, to launch and ongoing product health monitoring and troubleshooting. We have three programs – Ads Portal Foundation Systems (Ads Portal Framework, Ads Design System, Ads Portal Spoofing), Ads Portal Common Experience Systems (Ads Portal Navigation, Ads Notifications, Advertiser Feedback System) and Ads Portal Analytics & Science Framework (Telemetry, Observability, Experimentation, Insights). Our foundation charter builds common features that form the home for all Amazon Ads products and applications. It accelerates federated innovation and enables all builders to ship applications for customers globally while keeping the overall Ads Portal experience familiar. Experience charter builds and enhances marketer experiences across Ads Portal. Analytics & Science charter empowers builders to make data-informed product decisions through the next generation of analytics technologies and experimentation capabilities. It helps builders uncover the unknown by scientifically measuring customer experience at all stages of their journey within Ads self-serve and making it easily accessible. We seek a strong technical leader with domain expertise in machine learning and deep learning, transformers, generative models, large language models, computer vision and multimodal models. You will devise innovative solutions at scale, pushing the technological and science boundaries. You will guide the design, modeling, and architectural choices of state-of-the-art large language models and multimodal models. You will devise and implement new algorithms and new learning strategies and paradigms. You will be technically hands-on and drive the execution from ideation to productionization. You will work in collaborative environment with other technical and business leaders, to innovate on behalf of the customer. Key job responsibilities As a Principal Applied Scientist, you will have deep expertise in machine learning and data science, with specialties in large language models, reinforcement learning, supervised learning, and generative AI across various modalities. This role involves aligning solutions with multiple partners including product teams, experience design and foundational model teams. You will lead teams of scientists and engineers in translating business and functional requirements into concrete deliverables, driving strategic initiatives to enhance Gen AI driven advertiser experiences. Your responsibilities include designing integrated solutions that are efficiently implemented across all stakeholder teams, maintaining alignment in the short term while influencing long-term strategic roadmaps to support ongoing experimentation. You will ensure high solution quality, focusing on accurately understanding and responding to stakeholders, enhancing the speed of experiments and iterations of advertiser experience. Additionally, this role involves building scalable solutions with robust checks on human feedback, managing the complexities of user intents, and reinforcing learning algorithms with human feedback. You will make critical decisions on the best technical solutions for both immediate and future needs, clarify complex issues, manage trade-offs, and communicate effectively about technical challenges. Finally, you will work with academic partners to enhance our team's capabilities by accessing the latest research and expert mentoring, ensuring our approaches remain cutting-edge. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA
GB, London
"Are you a MS or PhD student interested in the fields of Computer Science or Operational Research? Do you enjoy diving deep into hard technical problems and coming up with solutions that enable successful products? If this describes you, come join our research teams at Amazon. " Key job responsibilities The candidate will be responsible for the design and implementation of optimization algorithms. The candidate will translate high-level business problems into mathematical ones. Then, they will design and implement optimization algorithms to solve them. The candidate will be responsible also for the analysis and design of KPIs and input data quality. About the team ATS stands for Amazon Transportation Service, we are the middle-mile planners: we carry the packages from the warehouses to the cities in a limited amount of time to enable the “Amazon experience”. As the core research team, we grow with ATS business to support decision making in an increasingly complex ecosystem of a data-driven supply chain and e-commerce giant. We take pride in our algorithmic solutions: We schedule more than 1 million trucks with Amazon shipments annually; our algorithms are key to reducing CO2 emissions, protecting sites from being overwhelmed during peak days, and ensuring a smile on Amazon’s customer lips. We do not shy away from responsibility. Our mathematical algorithms provide confidence in leadership to invest in programs of several hundreds millions euros every year. Above all, we are having fun solving real-world problems, in real-world speed, while failing & learning along the way. We employ the most sophisticated tools: We use modular algorithmic designs in the domain of combinatorial optimization, solving complicated generalizations of core OR problems with the right level of decomposition, employing parallelization and approximation algorithms. We use deep learning, bandits, and reinforcement learning to put data into the loop of decision making. We like to learn new techniques to surprise business stakeholders by making possible what they cannot anticipate. For this reason, we work closely with Amazon scholars and experts from Academic institutions. We are open to hiring candidates to work out of one of the following locations: London, GBR
US, MA, Boston
The Artificial General Intelligence (AGI) team is looking for a highly-skilled Senior Applied Scientist, to lead the development and implementation of cutting-edge algorithms and push the boundaries of efficient inference for Generative Artificial Intelligence (GenAI) models. As a Senior Applied Scientist, you will play a critical role in driving the development of GenAI technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities - Design and execute experiments to evaluate the performance of different decoding algorithms and models, and iterate quickly to improve results - Develop deep learning models for compression, system optimization, and inference - Collaborate with cross-functional teams of engineers and scientists to identify and solve complex problems in GenAI - Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the team We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA | Boston, MA, USA | New York, NY, USA