Newsletter
Follow Us

Sustainability call for proposals — Fall 2024

Welcoming proposals related to data validation, life cycle assessment, biodiversity and more.

Share

About this CFP

Amazon Sustainability works to make Amazon one of the most environmentally and socially responsible places to buy or sell goods and services. We conduct research to map, model and measure the end-to-end environmental and social impact of the company and vet sustainability topics that will have the greatest future impact to Amazon to inform business planning and resilience. We develop and test strategies that support revenue growth while reducing negative environmental and social impact. We work with the external science community to drive our vision and mission. We accelerate sustainability practices at Amazon by guiding critical decision makers with crisp recommendations backed by scientific rigor. We remove ambiguity around sustainability and provide them scientifically credible mechanisms, data, tools and solutions that they can use to make informed decisions.

We welcome proposals in the following research tracks:

Validating sustainability data at scale

Accurate and verifiable greenhouse gas (GHG) emissions data across the supply chain is critical for organizations to make informed procurement decisions, set meaningful carbon and other environmental impacts reduction targets, and drive meaningful progress towards their climate goals. However, the current process of validating supplier-reported GHG metrics is often manual, costly, and lacks consistency. Proving the accuracy of abatement data is further complicated by the complex and ever-changing nature of business operations. Key challenges include verifying that supplier-reported GHG emissions reductions adhere to established standards of being real, additional, and permanent, as well as socially-beneficial. We invite proposals for innovative, open-sourced projects that leverage machine learning (ML) and artificial intelligence (AI) techniques to improve data resolution and validate GHG emissions and carbon accounting data by harnessing data from diverse sources, including data shared by suppliers, with the goal of streamlining the process and lowering the overall cost of verification for all organizations. The validations should be sufficient for GHG emissions and carbon accounting claims. Where possible, we encourage proposals to incorporate current standards for producing (e.g., Product Category Rules) and sharing carbon data (e.g., WBCSD Pathfinder Initiative). Additional challenges include the difficulty in aggregating accurate, comparable GHG emissions data across complex, global supply chains due to inconsistent or costly data sharing practices, and the limited ability for organizations to quickly identify and address discrepancies or anomalies in supplier-reported carbon performance.

Machine learning applications for life cycle assessment

Life cycle assessment (LCA) is an instrumental method for corporations disclosing their environmental footprint. The primary challenges associated with corporate footprinting are scalability, automation, transparency, and lack of appropriate data to measure impacts of a wide range of products and services. Currently, much of the LCA work remains manual, and requires subject matter expertise. We solicit proposals that primarily focus on machine learning application in life cycle assessment ranging from to automating assessment and validation, completing life cycle inventories using approximation, computing product carbon footprint (PCF) in supply chain and BOM data, use of large language models (LLMs) and ontologies / knowledge graphs in LCA settings, and building tools to conduct scenario analysis and assess emissions abatement potential at a web-scale. As lack of groundtruth data is a perennial challenge in this field, proposals are encouraged to contribute open-source benchmark datasets and reduce reliance on large-scale, expensive data collection.

Data-driven sustainable product design and manufacturing

There is a lack of methods, tools, and systems to enable product manufacturers to incorporate sustainability performance metrics into decisions made across the product’s life cycle, from product development to manufacturing to post-use recovery and treatment. We are welcoming research proposals focused on innovative approaches to create, test, and implement decision support capabilities for multiple sustainability criteria (e.g., carbon, waste, and water) to increase the velocity and lower the cost of more sustainable product development. Proposals that demonstrate broad applicability across different product sectors, supply chain complexity, and manufacturing types (discrete and continuous) are highly encouraged.

Climate risk assessment

We invite proposals that leverage novel methods and modeling approaches to advance climate risk assessment and resilience at scale. Traditional methods for monitoring impacts/damages from climate hazards to point assets (e.g. buildings, infrastructure), linear assets (e.g. roads), and supply chains often require expert assessment and are limited in their ability to assess risk at a local level. We seek innovative proposals that utilize artificial intelligence, remote sensing (e.g. pre- and post-disaster imagery), and new modeling techniques to enhance the assessment of vulnerabilities (damage functions). Projects should demonstrate how the proposed approaches can enable scalable, high-resolution risk evaluation without relying on traditional expert assessments. Moreover, proposals investigating the application of emerging technologies to better assess climate-related risks to nature and forests are highly encouraged. Climate risks to forests threaten permanence of carbon storages, durability of nature-based solutions, biodiversity, and supply of commodities within supply chains. We are interested in proposals that use new methodologies to quantify climate-related reversal risks and risks to ecosystem services, for example the inter-connections between carbon, biodiversity, and climate risks. We strongly encourage open-source contributions.

Biodiversity

We request proposals that advance biodiversity measurement, monitoring, and impact assessment. Despite growing recognition of biodiversity risks, critical gaps remain in our ability to systematically quantify changes in ecosystems, species populations, and genetic diversity across spatial scales. Traditional methods for biodiversity assessment have limited scalability, often relying on sparse validation data and expert-driven scoring systems. We invite projects that harness in-situ and remote sampling, artificial-intelligence, and new statistical techniques to enable continuous, high-resolution, and reliable biodiversity tracking at local levels. Additionally, we encourage proposals that advance biodiversity impact quantification and attribution. Innovative approaches are needed to translate the tangible interactions between biodiversity and ecosystems, human systems, and organizations. We are interested in approaches that quantify biodiversity co-benefits of nature-based solutions and climate change mitigation strategies. We encourage open-source contributions and pathways enabling real-world implementation.

Lower-carbon cement and concrete

Amazon seeks research proposals to address a critical gap in validating lower-carbon cement and concrete innovations. Cement and concrete production is highly carbon-intensive, contributing significantly to global emissions. While new solutions emerge, a key challenge is the lack of standardized methods to confirm these new materials can be manufactured, transported, and placed as easily as existing products. We are interested in research that comprehensively evaluates the performance, workability, and constructability of lower-carbon cement and concrete mixes across the value chain. The goal is to generate data-driven evidence supporting broad adoption of sustainable alternatives. Proposals demonstrating collaborative industry partnerships and practical, scalable solutions are encouraged.

Responsible supply chain

Corporate Social Responsibility (CSR) within supply chains is a critical area of research, addressing the ethical, environmental, and social impacts of global supply networks. Traditional supply chain auditing practices, while prevalent, face significant challenges related to scalability, transparency, and the absence of universal evaluation standards. These audits often rely on manual data collection processes, limiting their effectiveness in addressing complex and dynamic social risks.
This call for papers seeks to explore fundamental and academic problems in CSR within supply chains. We invite research that advances the theoretical foundations of CSR in supply chains, particularly through the lens of data-driven approaches and machine learning. Topics of interest include, but are not limited to:

  • Development of universal standards and frameworks for CSR evaluation in global supply chains.
  • Methodologies for real-time social risk detection and hotspot analysis.
  • Predictive modeling for supplier risk assessment and compliance.
  • AI to support humans in performing audits, such as generating strategies and guidance.
  • Innovative strategies for automating and enhancing the transparency of social responsibility audits.
  • Theoretical exploration of the ethical implications of AI in CSR decision-making processes.

CO2 Mineralization

Carbon capture, utilization, and storage (CCUS) is a critical decarbonization lever across several hard-to-abate industrial sectors. However, the potential of carbon capture and storage (CCS) is constrained by the availability of suitable CO2 pipeline infrastructure and nearby geological storage sites. Carbon capture and utilization (CCU) technologies, such as ex-situ mineral carbonation, offer a viable alternative for industrial sites that lack underground storage infrastructure. Nevertheless, the potential of ex-situ carbon mineralization is also limited by the cost of carbonation and the availability of suitable feedstocks besides industrial waste materials. This call for proposals aims to identify solutions that can maximize the impact of mineral carbonation for permanent CO2 sequestration, for example the identification/development of direct carbonation of Mg-rich minerals, processes to broaden the application of magnesium carbonate (MgCO3) produced through mineral carbonation, or AI-driven models for optimization of ex-situ/superficial mineralization.

Timeline

Submission period: September 25, 2024 - November 13, 2024 (11:59PM Pacific Time)

Decision letters will be sent out February 2025

Award details

Selected Principal Investigators (PIs) may receive the following:

  • Unrestricted funds, from $50,000 to $100,000 USD
  • AWS Promotional Credits, up to $40,000 USD
  • Training resources, including AWS tutorials and hands-on sessions with Amazon scientists and engineers

Awards are structured as one-year unrestricted gifts. The budget should include a list of expected costs specified in USD, and should not include administrative overhead costs. The final award amount will be determined by the awards panel.

Eligibility requirements

Please refer to the ARA Program rules on the Rules and Eligibility page.

Proposal requirements

Proposals should be prepared according to the proposal template. In addition, to submit a proposal for this CFP, please also include the following information:

  • Description of the proposed solution and its innovative aspects
  • Explanation of how the project addresses the specified challenges
  • Plan for the development and implementation of the methodology or dataset
  • Potential impact on sustainability in the targeted sectors
  • Inclusion of Category Rules across Environmental Product Declarations and Product Environmental Footprints where applicable
  • List of open-source tools, datasets, or methodologies you plan to contribute to.
  • List of AWS ML tools you will use.

Selection criteria

Proposals will be reviewed by a panel of experts in machine learning, LCA, and sustainability. Proposals will be evaluated on the following:

  • Immediate and sizeable impact on carbon abatements (i.e., reducing greenhouse gases)
  • Practicality and scalability of the solutions that can support measurement validations
  • Feasibility and clarity of the proposed approach
  • Potential for widespread adoption and implementation
  • Feasibility to open source

Expectations from recipients

To the extent deemed reasonable, Award recipients should acknowledge the support from ARA. Award recipients will inform ARA of publications, presentations, code and data releases, blogs/social media posts, and other speaking engagements referencing the results of the supported research or the Award. Award recipients are expected to provide updates and feedback to ARA via surveys or reports on the status of their research. Award recipients will have an opportunity to work with ARA on an informational statement about the awarded project that may be used to generate visibility for their institutions and ARA.

How to apply
When you're ready to submit your proposal, use the button below and follow the instructions on the site.
Submit your proposal

Work with us

See more jobs See more jobs
Postdoctoral Scientist, Fulfillment Technology and Robotics
US, MA, Westborough
Amazon is looking for talented Postdoctoral Scientists to join our Fulfillment Technology and Robotics team for a one-year, full-time research position. The Innovation Lab in BOS27 is a physical space in which new ideas can be explored, hands-on. The Lab provides easier access to tools and equipment our inventors need while also incubating critical technologies necessary for future robotic products. The Lab is intended to not only develop new technologies that can be used in future Fulfillment, Technology, and Robotics products but additionally promote deeper technical collaboration with universities from around the world. The Lab’s research efforts are focused on highly autonomous systems inclusive of robotic manipulation of packages and ASINs, multi-robot systems utilizing vertical space, Amazon integrated gantries, advancements in perception, and collaborative robotics. These five areas of research represent an impactful set of technical capabilities that when realized at a world class level will unlock our desire for a highly automated and adaptable fulfillment supply chain. As a Postdoctoral Scientist you will be developing a coordinated multi-agent system to achieve optimized trajectories under realistic constraints. The project will explore the utility of state-of-the-art methods to solve multi-agent, multi-objective optimization problems with stochastic time and location constraints. The project is motivated by a new technology being developed in the Innovation Lab to introduce efficiencies in the last-mile delivery systems. Key job responsibilities In this role you will: * Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s diverse global science community. * Publish your innovation in top-tier academic venues and hone your presentation skills. * Be inspired by challenges and opportunities to invent new techniques in your area(s) of expertise.
Applied Scientist
US, CA, Santa Clara
Amazon is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help build industry-leading language technology. Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Processing (NLP), Generative AI, Large Language Model (LLM), Natural Language Understanding (NLU), Machine Learning (ML), Retrieval-Augmented Generation, Responsible AI, Agent, Evaluation, and Model Adaptation. As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services, as well as contributing to the wider research community. You will gain hands on experience with Amazon’s heterogeneous text and structured data sources, and large-scale computing resources to accelerate advances in language understanding. The Science team at AWS Bedrock builds science foundations of Bedrock, which is a fully managed service that makes high-performing foundation models available for use through a unified API. We are adamant about continuously learning state-of-the-art NLP/ML/LLM technology and exploring creative ways to delight our customers. In our daily job we are exposed to large scale NLP needs and we apply rigorous research methods to respond to them with efficient and scalable innovative solutions. At AWS Bedrock, you’ll experience the benefits of working in a dynamic, entrepreneurial environment, while leveraging AWS resources, one of the world’s leading cloud companies and you’ll be able to publish your work in top tier conferences and journals. We are building a brand new team to help develop a new NLP service for AWS. You will have the opportunity to conduct novel research and influence the science roadmap and direction of the team. Come join this greenfield opportunity! About the team AWS Bedrock Science Team is a part of AWS Utility Computing 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. About the team Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the 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.
Applied Scientist, Personalization
GB, MLN, Edinburgh
We’re looking for a Machine Learning Scientist in the Personalization team for our Edinburgh office experienced in generative AI and large models. You will be responsible for developing and disseminating customer-facing personalized recommendation models. This is a hands-on role with global impact working with a team of world-class engineers and scientists across the Edinburgh offices and wider organization. You will lead the design of machine learning models that scale to very large quantities of data, and serve high-scale low-latency recommendations to all customers worldwide. You will embody scientific rigor, designing and executing experiments to demonstrate the technical efficacy and business value of your methods. You will work alongside a science team to delight customers by aiding in recommendations relevancy, and raise the profile of Amazon as a global leader in machine learning and personalization. Successful candidates will have strong technical ability, focus on customers by applying a customer-first approach, excellent teamwork and communication skills, and a motivation to achieve results in a fast-paced environment. Our position offers exceptional opportunities for every candidate to grow their technical and non-technical skills. If you are selected, you have the opportunity to make a difference to our business by designing and building state of the art machine learning systems on big data, leveraging Amazon’s vast computing resources (AWS), working on exciting and challenging projects, and delivering meaningful results to customers world-wide. Key job responsibilities Develop machine learning algorithms for high-scale recommendations problems. Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative analysis and business judgement. Collaborate with software engineers to integrate successful experimental results into large-scale, highly complex Amazon production systems capable of handling 100,000s of transactions per second at low latency. Report results in a manner which is both statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment.
Manager, Applied Scientist
IN, TS, Hyderabad
Welcome to the Worldwide Returns & ReCommerce team (WWR&R) at Amazon.com. WWR&R is an agile, innovative organization dedicated to ‘making zero happen’ to benefit our customers, our company, and the environment. Our goal is to achieve the three zeroes: zero cost of returns, zero waste, and zero defects. We do this by developing products and driving truly innovative operational excellence to help customers keep what they buy, recover returned and damaged product value, keep thousands of tons of waste from landfills, and create the best customer returns experience in the world. We have an eye to the future – we create long-term value at Amazon by focusing not just on the bottom line, but on the planet. We are building the most sustainable re-use channel we can by driving multiple aspects of the Circular Economy for Amazon – Returns & ReCommerce. Amazon WWR&R is comprised of business, product, operational, program, software engineering and data teams that manage the life of a returned or damaged product from a customer to the warehouse and on to its next best use. Our work is broad and deep: we train machine learning models to automate routing and find signals to optimize re-use; we invent new channels to give products a second life; we develop highly respected product support to help customers love what they buy; we pilot smarter product evaluations; we work from the customer backward to find ways to make the return experience remarkably delightful and easy; and we do it all while scrutinizing our business with laser focus. You will help create everything from customer-facing and vendor-facing websites to the internal software and tools behind the reverse-logistics process. You can develop scalable, high-availability solutions to solve complex and broad business problems. We are a group that has fun at work while driving incredible customer, business, and environmental impact. We are backed by a strong leadership group dedicated to operational excellence that empowers a reasonable work-life balance. As an established, experienced team, we offer the scope and support needed for substantial career growth. Amazon is earth’s most customer-centric company and through WWR&R, the earth is our customer too. Come join us and innovate with the Amazon Worldwide Returns & ReCommerce team!
Applied Scientist , Amazon
US, WA, Seattle
Amazon Advertising operates at the intersection of eCommerce and advertising, and is investing heavily in building a world-class advertising business. We are defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products to improve both shopper and advertiser experience. With a broad mandate to experiment and innovate, we grow at an unprecedented rate with a seemingly endless range of new opportunities. The Ad Response Prediction team in Sponsored Products organization build advanced deep-learning models, large-scale machine-learning pipelines, and real-time serving infra to match shoppers’ intent to relevant ads on all devices, for all contexts and in all marketplaces. Through precise estimation of shoppers’ interaction with ads and their long-term value, we aim to drive optimal ads allocation and pricing, and help to deliver a relevant, engaging and delightful ads experience to Amazon shoppers. As the business and the complexity of various new initiatives we take continues to grow, we are looking for talented Applied Scientists to join the team. Key job responsibilities As a Applied Scientist II, you will: * Conduct hands-on data analysis, build large-scale machine-learning models and pipelines * Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production * Run regular A/B experiments, gather data, perform statistical analysis, and communicate the impact to senior management * Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving * Provide technical leadership, research new machine learning approaches to drive continued scientific innovation * Be a member of the Amazon-wide Machine Learning Community, participating in internal and external MeetUps, Hackathons and Conferences
Sr. Applied Scientist, Prime Video Peak Forecasting
US, WA, Seattle
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! In Prime Video READI, our mission is to automate infrastructure scaling and operational readiness. We are growing a team specialized in time series modeling, forecasting, and release safety. This team will invent and develop algorithms for forecasting multi-dimensional related time series. The team will develop forecasts on key business dimensions with optimization recommendations related to performance and efficiency opportunities across our global software environment. As a founding member of the core team, you will apply your deep coding, modeling and statistical knowledge to concrete problems that have broad cross-organizational, global, and technology impact. Your work will focus on retrieving, cleansing and preparing large scale datasets, training and evaluating models and deploying them to production where we continuously monitor and evaluate. You will work on large engineering efforts that solve significantly complex problems facing global customers. You will be trusted to operate with complete independence and are often assigned to focus on areas where the business and/or architectural strategy has not yet been defined. You must be equally comfortable digging in to business requirements as you are drilling into design with development teams and developing production ready learning models. You consistently bring strong, data-driven business and technical judgment to decisions. You will work with internal and external stakeholders, cross-functional partners, and end-users around the world at all levels. Our team makes a big impact because nothing is more important to us than delivering for our customers, continually earning their trust, and thinking long term. You are empowered to bring new technologies to your solutions. If you crave a sense of ownership, this is the place to be.
Senior Data Scientist - APS, Publisher Products
US, CA, Palo Alto
Amazon’s Advertising Technology team builds the technology infrastructure and ad serving systems to manage billions of advertising queries every day. The result is better quality advertising for publishers and more relevant ads for customers. In this organization you’ll experience the benefits of working in a dynamic, entrepreneurial environment, while leveraging the resources of Amazon.com (AMZN), one of the world's leading companies. Amazon Publisher Services (APS) helps publishers of all sizes and on all channels better monetize their content through effective advertising. APS unites publishers with advertisers across devices and media channels. We work with Amazon teams across the globe to solve complex problems for our customers. The end results are Amazon products that let publishers focus on what they do best - publishing. The APS Publisher Products Engineering team is responsible for building cloud-based advertising technology services that help Web, Mobile, Streaming TV broadcasters and Audio publishers grow their business. The engineering team focuses on unlocking our ad tech on the most impactful Desktop, mobile and Connected TV devices in the home, bringing real-time capabilities to this medium for the first time. As a Data Scientist in our team, you will collaborate directly with developers and scientists to produce modeling solutions, you will partner with software developers and data engineers to build end-to-end data pipelines and production code, and you will have exposure to senior leadership as we communicate results and provide scientific guidance to the business. You will analyze large amounts of business data, automate and scale the analysis, and develop metrics (like ROAS, Share of Wallet) that will enable us to continually delight our customers worldwide. As a successful data scientist, you are an analytical problem solver who enjoys diving into data, is excited about investigations and algorithms, can multi-task, and can credibly interface between technical teams and business stakeholders. Your analytical abilities, business understanding, and technical aptitude will be used to identify specific and actionable opportunities to solve existing business problems and look around corners for future opportunities. Your expertise in synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication will enable you to answer specific business questions and innovate for the future. Major responsibilities include: · Utilizing code (Apache, Spark, Python, R, Scala, etc.) for analyzing data and building statistical models to solve specific business problems. · Collaborate with product, BIEs, software developers, and business leaders to define product requirements and provide analytical support · Build customer-facing reporting to provide insights and metrics which track system performance · Communicating verbally and in writing to business customers and leadership team with various levels of technical knowledge, educating them about our systems, as well as sharing insights and recommendations
Senior Scientist in Residence, Amazon
IN, HR, Gurugram
Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced ML systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data 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 like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning team for India Consumer Businesses. Machine Learning, Big Data and related quantitative sciences have been strategic to Amazon from the early years. Amazon has been a pioneer in areas such as recommendation engines, ecommerce fraud detection and large-scale optimization of fulfillment center operations. As Amazon has rapidly grown and diversified, the opportunity for applying machine learning has exploded. We have a very broad collection of practical problems where machine learning systems can dramatically improve the customer experience, reduce cost, and drive speed and automation. These include product bundle recommendations for millions of products, safeguarding financial transactions across by building the risk models, improving catalog quality via extracting product attribute values from structured/unstructured data for millions of products, enhancing address quality by powering customer suggestions We are developing state-of-the-art machine learning solutions to accelerate the Amazon India growth story. Amazon India is an exciting place to be at for a machine learning practitioner. We have the eagerness of a fresh startup to absorb machine learning solutions, and the scale of a mature firm to help support their development at the same time. As part of the India Machine Learning team, you will get to work alongside brilliant minds motivated to solve real-world machine learning problems that make a difference to millions of our customers. We encourage thought leadership and blue ocean thinking in ML. Key job responsibilities Use machine learning and analytical techniques to create scalable solutions for business problems Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes Design, develop, evaluate and deploy, innovative and highly scalable ML models Work closely with software engineering teams to drive real-time model implementations Work closely with business partners to identify problems and propose machine learning solutions Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model maintenance Work proactively with engineering teams and product managers to evangelize new algorithms and drive the implementation of large-scale complex ML models in production Leading projects and mentoring other scientists, engineers in the use of ML techniques About the team International Machine Learning Team is responsible for building novel ML solutions that attack India first (and other Emerging Markets across MENA and LatAm) problems and impact the bottom-line and top-line of India business. Learn more about our team from https://www.amazon.science/working-at-amazon/how-rajeev-rastogis-machine-learning-team-in-india-develops-innovations-for-customers-worldwide
Applied Scientist II, Amazon Business
IN, HR, Gurugram
“Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work.” Please visit https://www.amazon.science for more information Amazon Business is one of Amazon’s fastest growing businesses, focused on enabling business customers to research, discover and buy business, industrial and scientific products in large catalogs. Our customers include individual professionals, businesses and institutions that buy products in bulk quantities to run their business smoothly. Business customers have different and more complex needs than the traditional Amazon customer base. We operate in the US, EU5, Canada, Japan and India. And we are continually expanding to new countries. We are looking for Applied Scientist with strong technical experience, who are passionate in building scientific driven solutions to be part of the Amazon Business organization. This is a great opportunity to innovate and provide the best customer experience in the entire journey of purchase, right from product discovery to post purchase experiences. This is your chance to make an impact of multi-trillion-dollars on your own. In this role, you will be a technical expert with significant scope and impact. You will work with Product Managers, Software Engineers, Data Engineers, and other Applied Scientists, to build new and enhance existing ML models to optimize customer experience. A successful Applied Scientist at Amazon has extreme bias for action and operates in a startup environment, with outstanding leadership skills, proven ability to build and manage medium-scale modeling projects, identify data requirements, build methodology and tools that are statistically grounded. We need great leaders to think big and design new solutions to solve complex problems using machine learning (ML) and natural language processing (NLP) techniques to improve our customers’ experience when using AB. We are seeking someone who can thrive in a fast-paced, high-energy and fun work environment where we deliver value incrementally and frequently. We value highly technical people who know their subject matter deeply and are willing to learn new areas. We look for individuals who know how to deliver results and show a desire to develop themselves, their colleagues, and their career." Key job responsibilities - Serve as a technical expert and leader in building new and enhancing existing ML models to optimize customer experience for Amazon Business - Work closely with cross-functional teams including Product Managers, Software Engineers, Data Engineers, and other Applied Scientists - Identify data requirements, build methodology, and develop statistically grounded tools and solutions using machine learning (ML) and LLM - Drive projects from ideation to execution with an emphasis on bias for action. - Stay up-to-date with the latest advancements in AI/ML and proactively identify opportunities to improve the customer experience A day in the life - Collaborate with product and engineering teams to understand business requirements and translate them into technical solutions - Conduct in-depth data analysis and feature engineering to build robust ML models - Prototype and test new ideas, iterate quickly, and deploy models to production - Monitor model performance, troubleshoot issues, and continuously optimize models - Share learnings and best practices with the broader team, contribute to innovation and publish research papers.
Applied Scientist II, Amazon Business
IN, KA, Bangalore
“Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work.” Please visit https://www.amazon.science for more information Amazon Business is one of Amazon’s fastest growing businesses, focused on enabling business customers to research, discover and buy business, industrial and scientific products in large catalogs. Our customers include individual professionals, businesses and institutions that buy products in bulk quantities to run their business smoothly. Business customers have different and more complex needs than the traditional Amazon customer base. We operate in the US, EU5, Canada, Japan and India. And we are continually expanding to new countries. We are looking for Applied Scientist with strong technical experience, who are passionate in building scientific driven solutions to be part of the Amazon Business organization. This is a great opportunity to innovate and provide the best customer experience in the entire journey of purchase, right from product discovery to post purchase experiences. This is your chance to make an impact of multi-trillion-dollars on your own. In this role, you will be a technical expert with significant scope and impact. You will work with Product Managers, Software Engineers, Data Engineers, and other Applied Scientists, to build new and enhance existing ML models to optimize customer experience. A successful Applied Scientist at Amazon has extreme bias for action and operates in a startup environment, with outstanding leadership skills, proven ability to build and manage medium-scale modeling projects, identify data requirements, build methodology and tools that are statistically grounded. We need great leaders to think big and design new solutions to solve complex problems using machine learning (ML) and natural language processing (NLP) techniques to improve our customers’ experience when using AB. We are seeking someone who can thrive in a fast-paced, high-energy and fun work environment where we deliver value incrementally and frequently. We value highly technical people who know their subject matter deeply and are willing to learn new areas. We look for individuals who know how to deliver results and show a desire to develop themselves, their colleagues, and their career." Key job responsibilities - Serve as a technical expert and leader in building new and enhancing existing ML models to optimize customer experience for Amazon Business - Work closely with cross-functional teams including Product Managers, Software Engineers, Data Engineers, and other Applied Scientists - Identify data requirements, build methodology, and develop statistically grounded tools and solutions using machine learning (ML) and LLM - Drive projects from ideation to execution with an emphasis on bias for action. - Stay up-to-date with the latest advancements in AI/ML and proactively identify opportunities to improve the customer experience A day in the life - Collaborate with product and engineering teams to understand business requirements and translate them into technical solutions - Conduct in-depth data analysis and feature engineering to build robust ML models - Prototype and test new ideas, iterate quickly, and deploy models to production - Monitor model performance, troubleshoot issues, and continuously optimize models - Share learnings and best practices with the broader team, contribute to innovation and publish research papers.
See more jobs
Amazon Research Awards.jpg

Amazon Research Awards

Collaborating with scientists around the world to fund research, share knowledge and encourage innovation.
Learn more
View from space of a connected network around planet Earth representing the Internet of Things.
Get more from Amazon Science
Subscribe to our monthly newsletter

Amazon.com | Conditions of Use | Privacy | © 1996-2025 Amazon.com, Inc. or its affiliates

Follow Us