Decarbonizing paper packaging

Amazon teams up with RTI International, Schlumberger, and International Paper on a project selected by the US Department of Energy to scale carbon capture and storage for the pulp and paper industry.

Amazon delivers billions of packages each year, and for these deliveries, we aim to use as little additional packaging as possible while still ensuring products arrive safely. When additional packaging is necessary, the majority of the packaging materials we use are made from paper. This includes boxes, paper mailers, and in some cases, paper bags. One of the sustainability benefits of using paper over other packaging materials, such as conventional plastics, is that paper is generally easier to recycle for our customers. However, as with any material produced at scale today, the production processes result in carbon emissions.

Related content
Amazon joins the US DOE’s Bio-Optimized Technologies to keep Thermoplastics out of Landfills and the Environment (BOTTLE™) Consortium, focusing on materials and recycling innovation.

The carbon emissions associated with paper packaging depend heavily on the type of paper mill, the processes and fuels used, and the grade of paper products produced. Currently, the most common type of containerboard paper mill in the US is a mixed paper mill that uses both virgin and recycled fiber. The recycled fiber generally comes from “old corrugated containers (OCC)”, which is a recycling stream that includes recycled boxes such as the Amazon boxes recycled by our customers. The virgin fiber is produced from wood chips that go through a chemical pulping process that breaks the bonds between the cellulose fibers in the wood and a glue-like substance called lignin that holds the fibers together. Containerboard paper mills that use both recycled and virgin fiber are the most common because of reduced energy demands, raw-material flexibility, cost effectiveness, and the regulatory environment.

For mills that use at least some virgin fiber to make paper, the process used to make the virgin fiber generates waste biomass that can be used as a fuel to reduce the reliance on fossil fuels. This waste biomass includes wood waste from debarking and chipping the wood and residual lignin (often called black liquor), a byproduct of the pulping process. When this waste biomass is used as a fuel for generating on-site steam and electricity, it generates what is called biogenic carbon emissions. Biogenic emissions are defined as CO2 emissions related to the natural carbon cycle, which include emissions resulting from the combustion of biological materials.

Biogenic emissions from the combustion of biomass release CO2 that was recently (in geological timeframes) sequestered by biological materials, such as plants. The US Environmental Protection Agency (EPA) does not include biogenic emissions in greenhouse gas (GHG) reporting and considers these emissions carbon neutral because of their negligible net contribution to atmospheric CO2 concentrations. This is in contrast to the carbon emissions associated with the burning of fossil fuels, which do contribute to reported GHG emissions.

Related content
Pioneering web-based PackOpt tool has resulted in an annual reduction in cardboard waste of 7% to 10% in North America, saving roughly 60,000 tons of cardboard annually.

In 2021, about 74% of the direct carbon emissions reported by the US pulp and paper sector were biogenic, with the remaining emissions coming from the use of fossil fuels. If these biogenic emissions are captured and permanently stored, instead of being released to the atmosphere, it enables the production of lower-carbon paper compared to traditional methods. By capturing and permanently storing biogenic carbon emissions, it is technically possible to sequester more biogenic carbon than the amount of fossil-based carbon released to the atmosphere as a result of the various industrial processes associated with paper production. This approach is generally referred to as bioenergy with carbon capture and storage (BECCS) and is considered by the Intergovernmental Panel on Climate Change (IPCC) as one of the key carbon dioxide removal technologies needed to limit global warming to 1.5°C above pre-industrial levels.

Stylized representations of a forest, cut logs, a paper mill, an energy plant, and decarbonized packaging boxes, showing (1) carbon flowing from the atmosphere to the forest and logs; (2) pulpwood, recycled boxes, and steam and electricity from the energy plant passing to the paper mill; (3) black liquor from the paper mill and woodwaste from the pulping process flowing to the energy plant; and sequestered carbon from the energy plant being stored underground.
Carbon flows for the production of paper with integrated carbon capture and storage.

Decarbonized paper packaging

Carbon capture and storage (CCS) technology, along with sustainably managed forests, together have the potential to create a paper industry that becomes a climate solution by sequestering more emissions than the industry is responsible for releasing to the atmosphere. Although CCS technologies show promise for helping reduce or even eliminate GHG emissions, these technologies have not yet been proven out at a larger scale.

Related content
Amazon advocates for updating carbon accounting to measure where renewable-energy projects will have the greatest impact.

To help accelerate the development and adoption of CCS, we assembled a multi-disciplinary team to develop and propose a concept to build a CCS plant at a containerboard mill operated by one of our packaging suppliers. The proposal was one of only four selected by the Office of Clean Energy Demonstrations in the US Department of Energy (DOE). Our team includes International Paper (IP), Schlumberger (SLB) for the design and engineering, and RTI International, the research organization that originally developed the carbon capture technology. RTI took the lead on the proposal submission.

The award is for up to $88 million, and if we are able to successfully complete all stages of this first-of-its-kind project (target date 2029), this large-scale demonstration facility will capture up to 120,000 metric tons of CO2 per year, a portion of which are biogenic emissions. A CCS plant of this size can enable an annual production of approximately 100,000 metric tons of decarbonized paper that can be used for future Amazon boxes and other packaging, benefiting both our customers and the environment.

Data on a virgin mill, a virgin-and-recycled mill, and a recycled mill, showing that, in all three, bioenergy with carbon capture and storage reduces carbon emissions significantly more than conventional carbon capture and storage.
This chart shows the impact of electrification, fuel switching, the use of bioenergy, and CCS on the cradle-to-gate greenhouse gas (GHG) emissions of containerboard paper produced from a virgin mill, mixed paper mill, and recycled mill. The analysis was performed using an internal Amazon decarbonization model based on US average data from FisherSolve®.

Carbon capture technologies

Carbon capture technologies absorb and separate CO2 from exhaust gases associated with combustion processes that burn fuels to generate thermal energy. There are three main approaches to how CO2 can be separated from exhaust gases: 1) pre-combustion capture, which involves absorbing the CO2 before the combustion is completed; 2) post-combustion capture, which involves absorbing the CO2 after the combustion process; and 3) oxyfuel combustion capture, which refers to burning the fuels in pure oxygen instead of air. With the oxyfuel approach, the exhaust gas is predominantly composed of CO2 and water vapor, enabling the CO2 to be easily separated. Each of these ways to absorb the CO2 varies in terms of efficacy, energy demand, and cost. The most well-developed approach is post-combustion capture.

Related content
Confronting climate change requires the participation of governments, companies, academics, civil-society organizations, and the public.

For post-combustion capture, the CO2 can be captured by a liquid or a solid material that likes to bind to CO2. For the liquid approach, a mixture of water and 20-30% of an amine compound is typically used to bind the CO2. The process begins with putting the water-amine mixture in contact with the exhaust gases to selectively absorb the CO2 from the gas stream. After the CO2 has been absorbed, the liquid mixture is heated in a different step to release the CO2. The separated CO2 can then be compressed for storage, and the amine can be regenerated for re-use. This water-amine liquid method is known for its efficacy, but it is also relatively energy intensive. Solid materials have shown equally good adsorption of CO2, but they also require relatively high amounts of energy to adsorb and release the CO2.

Over the past 13 years, RTI International has been developing a different water-amine liquid that has much less water and more amine to address the core challenges with the traditional water-amine solutions. By significantly reducing the water content in the amine-based liquid, RTI’s non-aqueous amine solvent (NAS) carbon capture technology is able to lower the energy requirements for the absorption-regeneration cycle by up to 36% compared to the traditional water-amine liquid.

In addition to reducing energy consumption, the NAS technology also minimizes operational risks and maintenance costs due to its extremely low corrosivity and enhanced physicochemical properties. RTI’s NAS process represents a step forward for industrial decarbonization. The deployment of RTI’s NAS technology through the awarded DOE project at IP’s Vicksburg containerboard mill can help demonstrate the scalability of this promising approach to carbon capture.

Amazon co-founded the Climate Pledge with a goal to reach net-zero carbon emissions across our operations by 2040, 10 years ahead of the Paris Agreement. We recognize that achieving this ambitious goal requires partnerships across all industries to explore and develop cutting-edge carbon reduction technologies, such as CCS. This project allows Amazon to work with one of its paper packaging suppliers to scale up and demonstrate RTI’s NAS technology to decarbonize the papermaking process. This project will also serve as the foundation for de-risking and scaling this technology more broadly in the pulp and paper industry and across other sectors, such as cement and steel.

Research areas

Related content

US, WA, Bellevue
Does the idea of creating technology solutions for delivering 11 Billion+ packages across the globe excite you? If yes, come join a fun-loving, diverse, and creative team at Amazon Last Mile! The vision of the team is "To create Earth’s safest, most adaptive, and efficient plans for Last Mile logistics". The Last Mile Delivery Technology team is instrumental in impacting customer satisfaction directly, by devising innovative ways to deliver packages quickly and cost-effectively to the customers, and at scale using Artificial Intelligence (AI), Machine Learning and Operations Research solutions. Last Mile Delivery Technology organization supports the design, planning and execution of last mile transportation for Amazon’s various parcel and grocery delivery programs. All these programs require a large number of decision support systems to operate at scale and serve our customers, spanning demand planning, jurisdiction planning, delivery channel and network design, capacity planning for on the road and under the roof at delivery stations, routing inputs and route optimization. While these decision support systems have thus far been approached through the lens of traditional optimization and machine learning, we are looking to re-envision this space and pursue Foundational AI research, to innovate and advance the state of these decision support systems. Specifically, we are looking to develop foundational models (including Large Language Models, Multimodal Language Models, Multimodal Models), and adaptations to serve last mile use cases. Beyond Amazon the work developed will spur new fundamental knowledge and innovation in the logistics space. Job Location : Bellevue WA or Austin TX. Key job responsibilities You have deep expertise in ML/AI, staying current with the latest research and techniques. You also invent or adapt new scientific approaches based on customer needs, producing high-quality research reports and contributing to peer-reviewed publications when appropriate You are a highly skilled software engineer whose work is consistently of high quality, meets industry standards, and incorporates best practices. You work semi-autonomously, contribute to operational excellence. You have strong interpersonal and leadership skills, effectively collaborating with your team, championing scientific advancements, onboarding new teammates, setting a high standard for your scientific contributions, and actively participating in the wider scientific community
US, TX, Austin
The Automated Reasoning Group in AWS Utility Computing is looking for a Senior Applied Scientist with experience in building scalable automated reasoning solutions that delight customers. You will be part of a world-class team building the next generation of automated reasoning tools and services. You will apply your knowledge to propose solutions, create software prototypes, and develop prototypes into production systems using software development tools. In addition, you will support and scale your solutions to meet the ever-growing demand of customer use. You have demonstrated leadership in automated reasoning positions in industry or academia, strong verbal and written communication skills, are self-driven and deliver high quality results in a fast-paced environment. Each day, hundreds of thousands of developers make billions of transactions worldwide on AWS. They harness the power of the cloud to enable innovative applications, websites, and businesses. Using automated reasoning technology and mathematical proofs, AWS allows customers to answer questions about security, availability, durability, and functional correctness. We call this provable security, absolute assurance in security of the cloud and in the cloud. https://aws.amazon.com/security/provable-security/ Key job responsibilities As a Senior Applied Scientist, you will help shape the definition and vision for applied science across teams within AWS. We have a diverse portfolio of projects that target protocol, code, and hardware verification, and leadership opportunities exist for: - Advance automated code-level reasoning and invariant synthesis and proof repair for cloud-scale web services. - Build new engines and extending foundational proof engines that apply to distributed systems. - Researching the application of automated reasoning to novel software applications. - Building automated reasoning solutions for critical AWS DSLs for architectural configuration, migration, code generation, and other areas. - Improving integration and user experience of tools to support large-scale adoption and use of automated reasoning techniques. You will work in an agile, startup-like development environment, where you are always working on the most important things, and you will design, implement, test, deploy and maintain innovative software solutions to transform service performance, durability, cost, and security. About the team About AWS Diverse Experiences AWS 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. 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. 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 & 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. 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. This team is part of AWS Utility Computing: Utility Computing (UC) AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.
US, WA, Seattle
We’re working to improve shopping on Amazon using the conversational capabilities of large language models, and are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. You'll be working with talented scientists and engineers to innovate on behalf of our customers. If you're fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey! Key job responsibilities We seek strong Applied Scientists 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.
US, WA, Seattle
The Worldwide Defect Elimination (WWDE) Science team in Amazon Customer Service builds state-of-the-art Artificial Intelligence (AI) models to enable defect-free shopping experiences for Amazon customers. We develop technology and mechanisms to discover, root cause, measure, and escalate defects for resolution before they impact a broader range of customers. We are looking for a creative problem solver and technically-skilled Research Scientist able and interested in building AI solutions to address customer issues at scale. The ideal candidate will lead the development of innovative solutions that identify, root cause, attribute, and summarize problems embedded in large volumes of customer feedback in different modalities. They will also utilize the latest advances in GenAI technology to explore billions of customer contacts and automate defect resolution workflows. As a part of this role, this candidate will collaborate with a large team of experts in the field and move the state of defect elimination research forward. This candidate should have a knack for leveraging AI to translate complex data insights into actionable strategies and can communicate these effectively to both technical and non-technical audiences. Key job responsibilities * Apply science models to extract actionable information from large volumes and varying modalities of customer feedback * Leverage GenAI/Large Language Model (LLM) technology for scaling and automating defect elimination 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 A day in the life If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan About the team The Worldwide Defect Elimination (WWDE) team's mission is to understand and resolve all issues impacting customers at scale. The WWDE Science team is a force multiplier within this group, helping to to apply science solutions to eliminate defects and enhance customer experience.
AE, Dubai
Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply cutting edge Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center at AWS is a new strategic team that helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, data scientists, engineers, and solution architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for ML Data Scientists capable of using GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. Key job responsibilities As an ML Data Scientist, you will * Collaborate with ML scientist and architects to Research, design, develop, and evaluate cutting-edge generative AI algorithms to address real-world challenges * Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production * Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder * Provide customer and market feedback to Product and Engineering teams to help define product direction
US, WA, Bellevue
We are seeking a passionate, talented, and inventive individual to join the Applied AI team and help build industry-leading technologies that customers will love. This team offers a unique opportunity to make a significant impact on the customer experience and contribute to the design, architecture, and implementation of a cutting-edge product. The mission of the Applied AI team is to enable organizations within Worldwide Amazon.com Stores to accelerate the adoption of AI technologies across various parts of our business. We are looking for a Senior Applied Scientist to join our Applied AI team to work on LLM-based solutions. We are seeking an experienced Scientist who combines superb technical, research, analytical and leadership capabilities with a demonstrated ability to get the right things done quickly and effectively. This person must be comfortable working with a team of top-notch developers and collaborating with our research teams. We’re looking for someone who innovates, and loves solving hard problems. You will be expected to have an established background in building highly scalable systems and system design, excellent project management skills, great communication skills, and a motivation to achieve results in a fast-paced environment. You should be somebody who enjoys working on complex problems, is customer-centric, and feels strongly about building good software as well as making that software achieve its operational goals. Key job responsibilities You will be responsible for developing and maintaining the systems and tools that enable us to accelerate knowledge operations and work in the intersection of Science and Engineering. You will push the boundaries of ML and Generative AI techniques to scale the inputs for hundreds of billions of dollars of annual revenue for our eCommerce business. If you have a passion for AI technologies, a drive to innovate and a desire to make a meaningful impact, we invite you to become a valued member of our team. A day in the life On our team you will push the boundaries of ML and Generative AI techniques to scale the inputs for hundreds of billions of dollars of annual revenue for our eCommerce business. If you have a passion for AI technologies, a drive to innovate and a desire to make a meaningful impact, we invite you to become a valued member of our team.
US, MA, Westborough
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 that work passionately to apply cutting edge advances in robotics and software to solve real-world challenges that will transform our customers’ experiences in ways we can’t even imagine yet. 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 Applied Science Interns and Co-ops with a passion for robotic research to work on cutting edge algorithms for robotics. Our team works on challenging and high-impact projects within robotics. Examples of projects include allocating resources to complete a million orders a day, coordinating the motion of thousands of robots, autonomous navigation in warehouses, identifying objects and damage, and learning how to grasp all the products Amazon sells. As an Applied Science Intern/Co-op at Amazon Robotics, you will be working on one or more of our robotic technologies such as autonomous mobile robots, robot manipulators, and computer vision identification technologies. The intern/co-op project(s) and the internship/co-op location are determined by the team the student will be working on. Please note that by applying to this role you would be considered for Applied Scientist summer intern, spring co-op, and fall co-op roles on various Amazon Robotics teams. These teams work on robotics research within areas such as computer vision, machine learning, robotic manipulation, navigation, path planning, perception, optimization and more. Learn more about Amazon Robotics: https://amazon.jobs/en/teams/amazon-robotics
IL, Tel Aviv
Are you a MS or PhD student interested in a 2024 Research Science Internship, where you would be using your experience to initiate the design, development, execution and implementation of scientific research projects? If so, we want to hear from you! Is your research in machine learning, deep learning, automated reasoning, speech, robotics, computer vision, optimization, or quantum computing? If so, we want to hear from you! We are looking for motivated students with research interests in a variety of science domains to build state-of-the-art solutions for never before solved problems You can find more information about the Amazon Science community as well as our interview process via the links below; https://www.amazon.science/ https://amazon.jobs/content/en/career-programs/university/science Key job responsibilities As a Research Science Intern, you will have following key job responsibilities; • Work closely with scientists and engineering teams (position-dependent) • Work on an interdisciplinary team on customer-obsessed research • Design new algorithms, models, or other technical solutions • Experience Amazon's customer-focused culture A day in the life At Amazon, you will grow into the high impact, visionary person you know you’re ready to be. Every day will be filled with developing new skills and achieving personal growth. How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow. Some more benefits of an Amazon Science internship include; • All of our internships offer a competitive stipend/salary • Interns are paired with an experienced manager and mentor(s) • Interns receive invitations to different events such as intern program initiatives or site events • Interns can build their professional and personal network with other Amazon Scientists • Interns can potentially publish work at top tier conferences each year About the team Applicants will be reviewed on a rolling basis and are assigned to teams aligned with their research interests and experience prior to interviews. Start dates are available throughout the year and durations can vary in length from 3-6 months for full time internships and up to 12 months for part time internships. This role may available across multiple locations in the EMEA region (Austria, Estonia, France, Germany, Ireland, Israel, Italy, Luxembourg, Netherlands, Poland, Romania, Spain, UAE, and UK). Please note these are not remote internships.
US, WA, Bellevue
The AGI Data Service team is seeking a dedicated, skilled, and innovative 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-DS team, a Research 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. A 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 The 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, the 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.
US, WA, Seattle
Join us in building on AWS, for AWS! Amazon Web Services (AWS) provides companies of all sizes with an infrastructure web services platform in the cloud (“Cloud Computing”). With AWS you can requisition compute power, storage, and many other services – gaining access to a suite of elastic IT infrastructure services as your business demands them. AWS is the leading platform for designing and developing applications for the cloud and is growing rapidly with hundreds of thousands of companies in over 190 countries on the platform. Developers all over the world rely on our storage, compute, and virtualized services. Our success depends on our world-class selling and field teams, and these teams rely on the Worldwide Sales Strategy and Operations (SMGS Ops) team to power their activities. We’re handling massive scale, providing data that drives the AWS business internally, and delivering products and services to help our Amazon Web Service selling teams, marketing groups, and customers. We’re looking for a Data Scientist to design and deliver solutions that combine machine learning, human-in-the-loop input, and distributed big data technologies. We're building a cutting-edge data platform to enable us to arm our field teams with the actionable intelligence needed to engage and serve every possible AWS customer in the world, to the fullest. This position may be based in Seattle, WA; Dallas, TX Key job responsibilities - Design solutions to complex and ambiguous data challenges, starting from first principles - Apply Machine Learning to solve data problems, such as record matching, at scale - Leverage company data from third-party sources in combination with internal AWS data to develop quantitative models answering critical business questions - Build human-in-the-loop workflows, to complement and augment ML solutions - Work with AWS machine learning and big data technologies such as Amazon Sagemaker, EMR, S3, DynamoDB, Lambda, and more - Experiment and explore new technologies to create innovative solutions - Use Natural Language Processing and language models to derive insights from unstructured sources like public company regulatory filings and annual reports About the team Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and we host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Our team also puts a high value on work-life balance. Striking a healthy balance between your personal and professional life is crucial to your happiness and success here, which is why we aren’t focused on how many hours you spend at work or online. Instead, we’re happy to offer a flexible schedule so you can have a more productive and well-balanced life—both in and outside of work. About AWS Diverse Experiences AWS 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. 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. 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 & 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. 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.