Neural networks

About Amazon Regulatory Intelligence, Safety, and Compliance (RISC). Amazon RISC’s vision is to make Amazon Earth’s most trusted shopping destination for safe and compliant products. Towards this mission, we take a science-first approach to building technology, products and services, that protect customers from unsafe, illegal, controversial, or policy-violating products. Job Summary We are seeking an exceptional Applied Scientist to join a team of experts in the field of machine learning, and work together to tackle challenging problems across diverse compliance domains. We leverage and train state-of-the-art multi-modal and large-language-models (LLMs) to detect illegal and unsafe products across the Amazon catalog. We work on machine learning problems for multi-modal classification, intent detection, information retrieval, anomaly and fraud detection, and generative AI. This is an exciting and challenging position to deliver scientific innovations into production systems at Amazon-scale to make immediate, meaningful customer impacts while also pursuing ambitious, long-term research. You will work in a highly collaborative environment where you can analyze and process large amounts of image, text and tabular data. You will work on hard science problems that have not been solved before, conduct rapid prototyping to validate your hypothesis, and deploy your algorithmic ideas at scale. There will be something new to learn every day as we work in an environment with rapidly evolving regulations and adversarial actors looking to outwit your best ideas. Key job responsibilities • Design and evaluate state-of-the-art algorithms and approaches in multi-modal classification, large language models (LLMs), intent detection, information retrieval, anomaly and fraud detection, and generative AI • Translate product and CX requirements into measurable science problems and metrics. • Collaborate with product and tech partners and customers to validate hypothesis, drive adoption, and increase business impact • Key author in writing high quality scientific papers in internal and external peer-reviewed conferences. A day in the life - Understanding customer problems, project timelines, and team/project mechanisms - Proposing science formulations and brainstorming ideas with team to solve business problems - Writing code, and running experiments with re-usable science libraries - Reviewing labels and audit results with investigators and operations associates - Sharing science results with science, product and tech partners and customers - Writing science papers for submission to peer-review venues, and reviewing science papers from other scientists in the team. - Contributing to team retrospectives for continuous improvements - Driving science research collaborations and attending study groups with scientists across Amazon About the team We are a team of applied scientists building AI/ML solutions to make Amazon Earth’s most trusted shopping destination for safe and compliant products.

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

Looking for your next challenge? North America Sort Centers (NASC) are experiencing growth and looking for a skilled, highly motivated Data Scientist to join the NASC Engineering Data, Product and Simulation Team. The Sort Center network is the critical Middle-Mile solution in the Amazon Transportation Services (ATS) group, linking Fulfillment Centers to the Last Mile. The experience of our customers is dependent on our ability to efficiently execute volume flow through the middle-mile network. Key job responsibilities The Data Scientist will design and implement solutions to address complex business questions using simulation. In this role, you will apply advanced analysis techniques and statistical concepts to draw insights from massive datasets, and create intuitive simulations and data visualizations. You can contribute to each layer of a data solution – you work closely with process design engineers, business intelligence engineers and technical product managers to obtain relevant datasets and create simulation models, and review key results with business leaders and stakeholders. Your work exhibits a balance between scientific validity and business practicality. On this team, you will have a large impact on the entire NASC organization, with lots of opportunity to learn and grow within the NASC Engineering team. This role will be the first dedicated simulation expert, so you will have an exceptional opportunity to define and drive vision for simulation best practices on our team. To be successful in this role, you must be able to turn ambiguous business questions into clearly defined problems, develop quantifiable metrics and deliver results that meet high standards of data quality, security, and privacy. About the team NASC Engineering’s Product and Analytics Team’s sole objective is to develop tools for under the roof simulation and optimization, supporting the needs of our internal and external stakeholders (i.e Process Design Engineering, NASC Engineering, ACES, Finance, Safety and Operations). We develop data science tools to evaluate what-if design and operations scenarios for new and existing sort centers to understand their robustness, stability, scalability, and cost-effectiveness. We conceptualize new data science solutions, using optimization and machine learning platforms, to analyze new and existing process, identify and reduce non-value added steps, and increase overall performance and rate. We work by interfacing with various functional teams to test and pilot new hardware/software solutions.

AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help. You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. Are you an experienced in sustainability science professional who is passionate about making a big impact? Are you interested in a high impact role at the world’s preeminent cloud computing company? The AWS Sustainability Science team is hiring a Sustainability Scientist. This role will support our Climate Pledge goal of net zero carbon by 2040 by developing scalable methods and models to assess and improve the environmental impacts of AWS data centers and cloud computing services from manufacturing, transportation, use, and end-of-life. This work will drive a deeper understanding of AWS’s environmental impacts, and enable strategic management of our carbon emissions. The ideal candidate will have industry experience in driving Life Cycle Assessments (LCAs) of products and services, possess a strong understanding of the GHG Protocol and carbon accounting practices, and have a detailed knowledge of manufacturing, design, development, and/or sourcing. The candidate should be comfortable working with imperfect data, identifying sources of uncertainty, and finding public data to fill the gaps where needed. The successful candidate must have strong analytical skills and the ability to apply systems thinking to complex, fast moving problems. The candidate should have familiarity with LCA methods and applications. The successful candidate will act as a subject matter expert, including designing research, gathering data, interpreting results, and developing metrics and reports. The candidate will coordinate with cross-functional project teams in gathering and analyzing large amounts of data. Key job responsibilities In this role you will be responsible for: * Serving as an AWS subject matter expert in Sustainability * Developing Life Cycle Assessment (LCA) methodologies to ensure AWS has an accurate and credible basis for sustainability efforts. * Developing internal LCA models for AWS infrastructure and services including server hardware and mechanical and electrical systems * Conducting LCAs including research, data collection, modeling, data analysis, data visualization, and reporting to quantify environmental impacts of our data centers and cloud computing services * Developing reports, dashboards and metrics which distill complex data into actionable insights to inform improvements * Building and developing relationships with internal and external stakeholders to drive programs to completion * Work closely with software engineering teams to drive real-time model implementations and new features * Having fun and working hard! A day in the life Each day you will interact with different teams responsible for all aspects of hardware and data centers. Your work will span the life cycle of our operations and allow you to influence how we develop and implement sustainability practices. You will have the opportunity to work on projects locally and globally. About the team Why AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship and Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Are you interested in changing the Digital Reading Experience? We are from Kindle Books Team looking for a set of Scientists to take the reading experience in Kindle to next level with a set of innovations! We envision Kindle as the place where readers find the best manifestation of all written content optimized with features that enable them to get the most out of reading, and creators are able to realize their vision to customers quickly and at scale. Every time customers open their content, regardless of surface, they start or restart their reading in a familiar, useful and engaging place. We achieve this by building a strong foundation of core experiences and act as a force multiplier and partner for content creators (directly or indirectly) to easily innovate on top of Kindle's purpose built content experience stack in a simple and extensible way. We will achieve this by providing a best-in-class reading experience, unique content experiences, and remaining agile in meeting the evolving needs and preferences of our users. Our goal is to foster long-lasting reading habits and make us the preferred destination for enriching literary experiences. We are building a In The Book Science team and looking for Scientists, who are passionate about Reading and are willing to take Reading to the next level. Every Book is a complex structure with different entities, layout, format and semantics, with more than 17MM eBooks in our catalog. We are looking for experts in all domains like core NLP, Generative AI, CV and Deep Learning Techniques for unlocking capabilities like analysis, enhancement, curation, moderation, translation, transformation and generation in Books based on Content structure, features, Intent & Synthesis. Scientists will focus on Inside the book content and semantically learn the different entities to enhance the Reading experience overall (Kindle & beyond). They have an opportunity to influence in 2 major phases of life-cycle - Publishing (Creation of Books process) and Reading experience (building engaging features & representation in the book thereby driving reading engagement). Key job responsibilities - 3+ years of building machine learning models for business application experience - PhD, or Master's degree and 2+ years of applied research experience - Knowledge of programming languages such as C/C++, Python, Java or Perl - Experience programming in Java, C++, Python or related language - You have expertise in one of the applied science disciplines, such as machine learning, natural language processing, computer vision, Deep learning - You are able to use reasonable assumptions, data, and customer requirements to solve problems. - You initiate the design, development, execution, and implementation of smaller components with input and guidance from team members. - You work with SDEs to deliver solutions into production to benefit customers or an area of the business. - You assume responsibility for the code in your components. You write secure, stable, testable, maintainable code with minimal defects. - You understand basic data structures, algorithms, model evaluation techniques, performance, and optimality tradeoffs. - You follow engineering and scientific method best practices. You get your designs, models, and code reviewed. You test your code and models thoroughly - You participate in team design, scoping and prioritization discussions. You are able to map a business goal to a scientific problem and map business metrics to technical metrics. - You invent, refine and develop your solutions to ensure they are meeting customer needs and team goals. You keep current with research trends in your area of expertise and scrutinize your results. A day in the life You will be working with a group of talented scientists on researching algorithm and running experiments to test solutions to improve our experience. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, model development and productionizing the same. You will mentor other scientists, review and guide their work, help develop roadmaps for the team.

Amazon is one of the most popular sites in the US. Our product search engine, one of the most heavily used services in the world, indexes billions of products and serves hundreds of millions of customers world-wide. Our team leads the science and analytics efforts for the search page and we own multiple aspects of understanding how we can measure customer satisfaction with our experiences. This include building science based insights and novel metrics to define and track customer focused aspects. We are working on a new measurement framework to better quantify and qualify the quality of the search customer experience and are looking for a Senior Applied Scientist to lead the development and implementation of different signals for this framework and tackle new and uncharted territories for search engines. This includes very ambiguous areas of quality where we would like to measure how customers perceive the results and take action to improve it. Key job responsibilities We are looking for an experienced Sr. Applied Scientist to lead signal development with an LLM influence and drive critical product decisions for Amazon Search. We are developing new ways we measure customer satisfaction with the quality of the search page including translating their perception into large scale quantitative metrics. LLMs will be one powerful tool in our toolkit. You will design and build AI based science solutions to allow routine inspection and deep business understanding as the search customer experience is being transformed. These metrics and signals will be made available for downstream teams to use as features in their decision making model or optimization systems. Your desire to learn and be curious will help us look around corners for improvement opportunities and more efficient metrics development. In this role, you will partner with data engineers, business intelligence engineers, product managers, software engineers, economists, and other scientists. About the team The mission of the Search Data Science team is to build a world class shopping experience that delights customers. We focus on the long term and big picture, ensuring that the search page is balancing strategic trade-offs. We bring to this effort expertise in constrained optimization, causal inference, and marketplace equilibrium effects. We build systems, metrics, and mechanisms to ensure that product decisions are scientifically sound. We develop models to estimate the downstream dollar value of the quality of the experience. We spend time on evaluating experiments to develop durable learnings.

Are you a data enthusiast? Do the world's most complex data and analytics systems and advancements in generative AI and LLMs inspire your curiosity? Is your passion to navigate through hundreds of systems, processes, and data sources to solve the puzzles and identify the next big opportunity? Are you a creative big thinker who is passionate about using data and optimization tools to direct decision-making and solve complex and large-scale challenges? Do you feel like your skills uniquely qualify you to bridge communication between teams with competing priorities? If so, then this position is for you! We are looking for a motivated individual with strong analytical and communication skills to join the effort in advancing our work in PXT from the data and analytics capabilities we have today to what will be essential tomorrow. This magnificent challenge is a terrific opportunity to analyze Amazon’s data and generate actionable recommendations using optimization and simulation. Come build with us! In this role, your main focus will be to perform analysis, synthesize information, identify business opportunities, provide project direction, and communicate business and technical requirements within the team and across stakeholder groups. You will consider the day-to-day needs of our continuously evolving analytics world and insist on the standards required to build automated and scalable solutions for tomorrow. You will assist in defining trade-offs and quantifying opportunities for a variety of projects. You will learn current processes, build metrics, educate diverse stakeholder groups, assist in initial solution design, and audit all model implementations. A successful candidate in this position will have a background in communicating across significant differences, prioritizing competing requests, and quantifying decisions made. The ideal candidate will have a strong ability to model real-world data with high complexity and deliver high-quality analysis, data products, and optimization models for strategic decisions. They are excited to be part of, and learn from, a large tech and non-tech team, ready to dig into the details to find insights that direct decisions. The successful candidate will have good communication skills and an ability to speak at a level appropriate for the audience, and will collaborate effectively with scientists, product managers, and business stakeholders. Key job responsibilities • Demonstrate thorough technical knowledge on feature engineering of massive datasets, effective exploratory data analysis, and model building using industry standard AI/ML models and working with Large Language Models. • Discover causal relationships in our data and recommend independent variables to be used in predictive and prescriptive analyses. • Proficiency in both Supervised (Linear/Logistic Regression) and Unsupervised algorithms (k means clustering). • Understand the business reality behind large sets of data and develop meaningful solutions comprising of analytics as well as marketing management. • Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area. • Innovate by adapting new modeling techniques and procedures. Process large scale datasets using distributed computing platform to build models, mining insights from data and prototyping models that optimize towards various business goals and metrics. • Passionate about working with huge data sets (training/fine tuning) and be someone who loves to bring datasets together to answer business questions. You should have deep expertise in creation and management of datasets. • Exposure at implementing and operating stable, scalable data flow solutions from production systems into end-user facing applications/reports. These solutions will be fault tolerant, self-healing and adaptive. • Work with distributed machine learning and statistical algorithms to harness enormous volumes of data at scale to serve our customers. • Interact with cross-functional teams and make business recommendations i.e., cost-benefit, forecasting, experiment analysis and present findings to leadership team. About the team Amazon Stores People Experience Technology (PXT) Analytics Team owns and creates the necessary data modeling to facilitate reporting and analytics, acquire new data sources, and build comprehensive data visualizations across the employment lifecycle, including promotions, retention, and transfers within the Amazon Stores Organization. The team owns the provision of Descriptive, Diagnostic, Predictive, and Prescriptive Analytics for the PXT Talent Management (TM) organization and beyond. Carrying the leaders, employees, and customers through the different transformational stages of data analytics, reporting and program implementation to drive deep learnings, process improvements, and strategic recommendations through employee data.

Amazon.com strives to be Earth's most customer-centric company where people can find and discover anything they want to buy online. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Are you seeking an environment where you can drive innovation? Do you want to apply learning techniques and advanced mathematical modeling to solve real world problems? Do you want to play a key role in the future of Amazon's Retail business? This job for you! The Customer Behavior Analytics (CBA) team at Amazon is responsible for the architecture, design, implementation of tools used to understand customer behavior and value generation for all Amazon programs. Come and join us! Amazon’s CBA team is looking for Economists, who can work at the intersection of economics, statistics and machine learning; and leverage the power of big data to solve complex problems like long-term causal effect estimation. Key job responsibilities Economists at Amazon are expected to work directly with other Economists and senior management on key business problems in retail, international retail, cloud computing, third party merchants, search, Kindle, streaming video, and operations. Amazon economists will apply the frontier of economic thinking to market design, pricing, forecasting, program evaluation, online advertising and other areas. You will build econometric models, using our world class data systems, and apply economic theory to solve business problems in a fast moving environment. Economists at Amazon will be expected to develop new techniques to process large data sets, address quantitative problems, and contribute to design of automated systems around the company.

Come be a part of a rapidly expanding $25 billion-dollar global business! At Amazon Business (AB), we set out every day to innovate and disrupt the status quo. We stand at the intersection of tech and retail in the B2B space developing innovative purchasing and procurement solutions to help businesses and organizations reimagine 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, unlocking our potential worldwide Key job responsibilities We are looking for a Sales Operations Leader – Data Science and Intelligence who will: • Lead the Sales Operations Intelligence Team – a cross-functional team of data scientists, engineers and operations managers. • Hire, Grow and Develop top tier operations, science and engineering talent. • Apply business judgement to identify opportunities and develop science strategies • Support Senior Leadership with all Sales Operations Intelligence strategy, and guidance, and run the management cadence for the business. • Collaborate on the design, development, maintenance, and delivery/presentation of predictive models, metrics, reports, analyses, and dashboards to drive key business decisions. • Work with leaders, partner teams, and finance to lead the annual quota, goals, budgeting, and ongoing forecasting processes. • Lead the development of routine and ad-hoc analytic reports to senior management regarding Business Development initiatives, customer segment performance, performance against goals, etc. • Ensure leadership reports include business insight for decision-making and minimize overall report burden. • Lead the modeling and development of recommendations for go-to-market execution. • Maintain thorough knowledge of existing and emerging 3rd party data sources as needed for analytics. • Responsible for the cycle of creating and posting content, iterating based on feedback, and reinforcing in Senior Leadership events (written and verbal). • Focus on seller experience to ensure programs are tailored to meet varied tenure, industry, and development requirements. • Support regular cadence of feedback and reviews of initiatives with sales leaders and managers **The preferred location for this position is Arlington, VA (HQ2). A day in the life The ideal candidate for this role is someone who builds the operational capabilities for Amazon Business sales by developing and implementing programs, tools and analytics to increase sales productivity. This role leads four pillars Sales Operations, Data Optimization & Modernization, Business Solutions & Support, and Intelligence, Design, Execution, and Automation. This role provides oversight as the “COO of Sales” and provides dedicated support with operational mechanisms, ad hoc projects/analysis, managing the sales pipeline, business reviews, account segmentation, and tools/systems improvements. This role leads CPS-wide seller productivity and customer segmentation. This role also builds simplified yet comprehensive datasets with dynamic dashboards to power self-service analytics and automated reporting which includes a global data model. For Business Solutions and Support, this role manages first-party (1P) and third-party (3P) Sales Tools and Sales Planning, which creates predictive growth forecasts for sales territories across North America. These models will directly inform incentive programs and performance measurement. About the team Amazon Business represents an incredible opportunity to address a vast new market segment and customer base. We are focused on building solutions that enable businesses to find, research, and buy products and services from a vast selection, across multiple devices, marketplaces and regions. Our customers include all types of businesses ranging from individual professionals to small businesses to large institutions (and everything in between). Our business customers have different needs than the traditional Amazon customers so we are reinventing everything from how we display our selection, price our products, and provide the right customer experience.

The Amazon Web Services (AWS) Marketing Science team seeks an Applied Scientist with a strong background in machine learning and production level software engineering to spearhead the advancement and deployment of cutting-edge ML systems. As part of this team, you will collaborate with talented peers to create scalable solutions to measure and optimize AWS events, advertising, and customer engagements to optimize investments, and inform decisions across marketing and sales. You will work on high-impact, high-visibility products, with your work improving the experience of AWS leads and customers. The ideal candidate possesses solid understanding of machine learning fundamentals, has experience writing high quality software in production setting, and experience or interest in causal inference and causal ML. The candidate is self-motivated, thrives in ambiguous and fast-paced environments, possesses the drive to tackle complex challenges, swiftly delivering impactful solutions while iterating on science and user feedback, develops strong working relationships and thrives in a collaborative team environment. Key job responsibilities * Analyze, understand, and model customer behavior based on large scale data * Lead the design, development, deployment, and innovation of advanced science models in the strategic area of marketing measurement and optimization * Design, build, and deploy effective and innovative ML solutions to improve components of our ML and causal inference pipelines * Build and deploy automated model training and evaluation pipelines * Research and implement novel deep learning, reinforcement learning, and/or machine learning based algorithms to deliver insights on customer behavior * Influence long-term science initiatives and mentor other scientists across AWS