A child sits in a chair at a kitchen counter, wearing headphones while watching a Fire tablet
As children spend more hours in front of screens, it is increasingly important to investigate the effects of digital technology. Boston Children’s Hospital launched the Digital Wellness Lab, a research center providing science-based recommendations for parents and caretakers.

Amazon Kids links up with Boston Children’s Hospital’s Digital Wellness Lab

Science-based recommendations from the Digital Wellness Lab could inform the development of digital products that help children.

Parents worldwide are confronted with a similar question: What is the impact of screen time in the lives of their children?

As children spend more hours in front of screens, it becomes increasingly important to investigate the effects of digital technology on their brains, bodies, and behaviors.

To assist that effort, experts at Boston Children’s Hospital recently launched the Digital Wellness Lab, a research center providing practical, science-based recommendations for parents and caretakers on how to raise healthy children in the digital age.

Amazon Kids, one of the supporters of the initiative, provides free tools for parents to make choices about how their children interact with devices such as Amazon Fire tablets, Kindle e-readers, Echo smart speakers, and Fire TV.

The team says it hopes to utilize Digital Wellness Lab research as it continues to develop new products that help children explore quality content online while informing and empowering parents.

Officially launched in March, the Digital Wellness Lab is an evolution of the Center on Media and Child Health at Boston Children's Hospital, which had been investigating the impact of media use on children’s mental and physical health for almost 20 years.

Michael Rich and David Bickham
Michael Rich, left, is the founder and director of the Digital Wellness Lab. David Bickham, right, is the lab's research scientist lead.
Glynis Condon

For the past couple of decades, the amount and the quality of research in this field has increased significantly, but its results remained mostly restricted to academia.

“It struck me that, no matter how wonderful our research was, until we got it into the hands of the people who could actually change the digital environment, we were going to be spinning our wheels,” said pediatrician Michael Rich, the lab’s founder and director.

He notes that while the tech industry is highly competitive, this is a topic where companies are collaborating to address the common concern over impact of technology on children. The Digital Wellness Lab originated from the idea that, by working together with industry, science could foster real change in devices, platforms, and software in ways to promote the wellness of individuals and society.

Amazon Kids’ support for science

Karen Ressmeyer, Amazon Kids director of Family Trust, describes the alliance with the Digital Wellness Lab as a win-win situation.

“This collaboration provides us with new insights and data from the lab to help our mission of contributing to a positive digital environment,” she said.

The goal of Amazon Kids and Amazon Kids+ — a subscription service providing access to thousands of books, movies, TV shows, and educational curated content — is to give children the freedom to explore high-quality content in a kid-friendly environment within parameters set by their parents or caretakers.

Karen Ressmeyer, left, is Amazon Kids director of Family Trust. Catherine Teitelbaum, right,
Karen Ressmeyer, left, is Amazon Kids director of Family Trust. Catherine Teitelbaum, right, is principal, Family Trust at Amazon Kids.
Glynis Condon

Working with the Digital Wellness Lab furthers that goal in a unique fashion, according to Catherine Teitelbaum, principal, Family Trust at Amazon Kids. “With this partnership we are intentionally creating a forum to discuss ideas of all sizes and learn from researchers, academics, and clinicians as we look to constantly strengthen our commitment to the wellness of kids and families,” she said.

While tech companies like Amazon can conduct research on their own to address concerns about the impact of technology on children’s mental health, this arrangement offers the ability to develop fundamental research that is completely independent and agnostic to outcomes, noted Rich.

“Our goal is to offer a resource that can inform both sides of the paradigm — the producers and the consumers — to move what they create and what they consume toward a better place in terms of physical, mental and social health,” he said.

Investigating how technology affects children

At the moment, one of the main research questions related to wellness and technology is how the COVID-19 pandemic has changed the use of technology by children.

One of the first efforts by the Digital Wellness Lab was a national survey with parents of children from kindergarten to grade 12 that showed as kids’ media use increased during the pandemic, so did the frequency of arguments with their parents over that usage. However, the survey found that spike did not owe purely to kids streaming videos.

“We also found that over 70% of children were using these devices to connect with their family and their friends, and this was true across all age groups,” said David Bickham, research scientist lead at the Digital Wellness Lab. When asked if media use was helpful or hurtful for their children, more than half of the parents said it was helpful for their social relationships and educational achievements.

That more nuanced understanding is a departure from the historically high degree of polarization around this topic, Rich observed. “You were either for kids or for screens, but you couldn't be for both,” he said. Having had an earlier career as a screenwriter and filmmaker – which included working as assistant director to Akira Kurosawa in Japan – he knew that people who were making media were not out to hurt kids.

Bickham noted that, rather than trying to label whether media use is fundamentally good or bad, the lab is trying to identify these types of nuances.

Open research questions

Historically, this field of research hasn’t determined clear causal relationships between types of screen use and mental and physical health outcomes, which constitutes an important gap, according to Rich.

What we want to do is start to move from correlations to understanding what type of screen use contributes to which outcomes.
Michael Rich

“For example, we don't know whether playing violent video games makes kids more violent, or whether more violent kids are drawn to violent video games,” he explained. “We just see correlations, and what we want to do is start to move from correlations to understanding what type of screen use contributes to which outcomes.”

The way to get there, notes Rich, is through long-term longitudinal studies, a type of research that follows the subjects for several years and collects data on different variables periodically. The Digital Wellness Lab has a project to do exactly that. The Growing Up Digital project is a 10-year longitudinal study that plans to have at least one site in each of the six populated continents.

“We are going to follow two cohorts of children, from preschool to middle school, and from middle school to young adulthood, on an annual basis measuring in a deep way not just the screens they are actively using, but also those they are ambiently exposed to,” Rich noted.

The study will measure several outcomes related to learning, mental health, and physical health, such as sleep, exercise and nutrition.

The program is already underway in Australia and Canada, and the group is having conversations with institutions from countries like India and Brazil to set up the study in those geographies as well.

bchimage.png
The Digital Wellness Lab is an evolution of the Center on Media and Child Health at Boston Children's Hospital.
Courtesy of Boston Children's Hospital

The lab also hopes to look at how the use of technology differs across cultures. Previous work by the group looked into digital media usage and play in young children from the United States and Mexico. While, in the U.S., “media use may have displaced time dedicated to certain types of play,” the opposite was true in Mexico: “play seemed to facilitate or positively co-occur with media use.”

“When you think about not just the amount of time spent with screens, but the characteristics of technology use and cultural differences, you start to reveal a more nuanced understanding of how technology impacts kids and their development,” Bickham said.

According to Rich, researchers in this field are coming to realize that it's not about the total duration of screen use, but what we are doing on the screens and the context in which we are doing it. In order to empower families to evaluate what type of technology use is healthy for their children, the lab recently published the Family Digital Wellness Guide, which gives science-based practical advice on the topic for parents and caretakers.

Empowering families is also one of the main goals of Amazon Kids.

“That is so closely tied with our focus at Amazon Kids,” said Teitelbaum, “where we have a long history of building not just products that are safe for kids and designed for kids, but engaging with parents through our parent dashboard, providing them choices to shape their children’s use of media.”

Related content

US, WA, Seattle
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. As a core product offering within our advertising portfolio, Sponsored Products (SP) helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The SP team's primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! Within Sponsored Products, the Bidding team is responsible for defining and delivering a collection of advertising products around bid controls (dynamic bidding, bid recommendations, etc.) that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven fundamentally from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. Key job responsibilities • Lead a new initiative across Sponsored Products Bidding focused on AI/ML based features. • Be the technical leader in AI, Machine Learning; lead efforts within this team and across other teams. • Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience. • Drive end-to-end AI/Machine Learning projects that have a high degree of ambiguity, scale, complexity. • Build models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your AI/ML models. • Run A/B experiments, gather data, and perform statistical analysis. • Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. • Research new and innovative AI/ machine learning approaches. A day in the life Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon's Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. About the team The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through the latest generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. The SPB Bidding team within Sponsored Products and Brands is focused on guiding and supporting Millions of advertisers to meet their advertising needs of creating and managing ad campaigns. At this scale, the complexity of diverse advertiser goals, campaign types, and market dynamics creates both a massive technical challenge and a transformative opportunity: even small improvements in bidding systems can have outsized impact on advertiser success and Amazon’s retail ecosystem. Our vision is to build a highly personalized, context-aware bidding system that leverages auction simulations, ML models, and optimization algorithms. This framework, will operate across SPB bidding system and proactively delivering value based on deep understanding of the advertiser. To execute this vision, we collaborate closely with stakeholders across Ad Console, Sales, and Marketing to identify opportunities—from high-level product guidance down to granular recommendations—and deliver them through a tailored, personalized experience. Our work is grounded in state-of-the-art bidding agent architectures, tool integration, reasoning frameworks, and model customization approaches (including tuning and preference optimization), ensuring our systems are both scalable and adaptive.
US, WA, Bellevue
Have you ever ordered a product on Amazon and when that box with the smile arrived you wondered how it got to you so fast? Have you wondered where it came from and how much it cost Amazon to deliver it to you? Have you also wondered what are different ways that the transportation assets can be used to delight the customer even more. If so, the Amazon transportation Services, North America Sort Center Science team is for you . We manage the delivery of tens of millions of products every week to Amazon’s customers, achieving on-time delivery in a cost-effective manner. We are looking for an enthusiastic, customer obsessed Applied Scientist with strong scientific thinking, good software and statistics experience, skills to help manage projects and operations, improve metrics, and develop scalable processes and tools. The primary role of an Applied Scientist within Amazon is to address business challenges through building a compelling case, and using data to influence change across the organization. This individual will be given responsibility on their first day to own those business challenges and the autonomy to think strategically and make data driven decisions. Decisions and tools made in this role will have significant impact to the customer experience, as it will have a major impact on how we operate the middle mile network. Ideal candidates will be a high potential, strategic and analytic graduate with a PhD in (Operations Research, Statistics, Engineering, and Supply Chain) ready for challenging opportunities in the core of our world class operations space. Great candidates have a history of operations research, machine learning , and the ability to use data and research to make changes. This role requires robust skills in research and implementation of scalable products and models . This individual will need to be able to work with a team, but also be comfortable making decisions independently, in what is often times an ambiguous environment. Key job responsibilities Key job responsibilities - Design and develop advanced mathematical optimization and machine learning solutions in the domains of network design and optimization. - Research, prototype, simulate, and experiment with these models using programming languages such as Java and Python; participate in the production level deployment. - Create, enhance, and maintain technical documentation and science designs. - Present to other Scientists, Product, and Software Engineering teams, as well as Stakeholders. - Lead project plans from a scientific perspective by managing product features, technical risks, milestones and launch plans.
US, CA, Sunnyvale
We are seeking a Applied Scientist to focus on Robot Navigation. In this role, you'll research and develop advanced navigation systems that enable robots to move reliably and safely through complex, dynamic environments. You'll work across a broad spectrum of navigation approaches—from classical methods to learning-based techniques and foundation models—to build robust solutions for autonomous robot navigation. Key job responsibilities - Develop and implement robust navigation systems that enable reliable autonomous operation in complex, dynamic indoor environments with static and dynamic obstacles - Build simulation-based and on-device evaluation frameworks with comprehensive benchmarks and metrics for systematic comparison of navigation methods - Conduct sim-to-real transfer experiments, analyzing performance gaps and developing techniques to ensure reliable real-world navigation performance - Collaborate with world model, manipulation, and other teams to ensure seamless integration of navigation capabilities into the full robot system - Stay current with the latest advances in robot navigation, spatial reasoning, and related fields, and apply relevant findings to improve system performance - Mentor fellow scientists and engineers while maintaining strong individual technical contributions About the team Fauna Robotics, an Amazon company, is building capable, safe, and genuinely delightful robots for everyday life. Our goal is simple: make robots people actually want to live and interact with in everyday human spaces. We believe that future won’t arrive until building for robotics becomes far more accessible. Today, too much effort is spent reinventing the fundamentals. We’re changing that by developing tightly integrated hardware and software systems that make it faster, safer, and more intuitive to create real-world robotic products.
US, CA, Sunnyvale
We are seeking a Senior Applied Scientist to focus on Robotics Spatial Intelligence and Semantic Understanding. In this role, you'll research and build advanced semantic and world understanding algorithms that enable robots to observe, understand, and reason about complex and dynamic home environments. You'll work across a broad spectrum of 3D perception, contextual understanding, and world modeling approaches to build robust solutions that support autonomous decision making, task planning, navigation, and manipulation. Key job responsibilities - Develop and implement robust World Understanding and Modeling algorithms for a domestic robot. - Build simulation-based and on-robot evaluation frameworks with comprehensive benchmarks and metrics for systematic evaluation of Our Spatial Intelligence stack. - Conduct sim-to-real transfer experiments, analyzing performance gaps and developing techniques to ensure reliable real-world performance. - Collaborate with navigation, manipulation, and other teams to ensure seamless integration of World Understanding capabilities. - Stay current with the latest advances in World Modeling, Spatial Reasoning, and related fields and apply relevant findings to improve system performance About the team Fauna Robotics, an Amazon company, is building capable, safe, and genuinely delightful robots for everyday life. Our goal is simple: make robots people actually want to live and interact with in everyday human spaces. We believe that future won’t arrive until building for robotics becomes far more accessible. Today, too much effort is spent reinventing the fundamentals. We’re changing that by developing tightly integrated hardware and software systems that make it faster, safer, and more intuitive to create real-world robotic products. Our work spans the full stack: mechanical design, control systems, dynamic modeling, and intelligent software. The focus is not just functionality, but experience. We’re building robots that feel responsive, expressive, and genuinely useful. At Fauna, you’ll work at the frontier of this space, helping define how robots move, manipulate, and interact with people in natural environments. It’s an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you.
GB, London
Come build the future of entertainment with us. Are you interested in shaping the future of movies and television? Do you want to define the next generation of how and what Amazon customers are watching? Prime Video is a premium streaming service that offers customers a vast collection of TV shows and movies — all with the ease of finding what they love to watch in one place. We offer customers thousands of popular movies and TV shows from Originals and Exclusive content to exciting live sports events. We also offer our members the opportunity to subscribe to add-on channels which they can cancel at anytime and to rent or buy new release movies and TV box sets on the Prime Video Store. Prime Video is a fast-paced, growth business — available in over 240 countries and territories worldwide. The team works in a dynamic environment where innovating on behalf of our customers is at the heart of everything we do. If this sounds exciting to you, please read on. Prime Video Commerce's mission is to present the right offer to the right customer at the right time — across subscriptions, channels, and transactional video, in every market and on every device. Our science team replaces static business rules with ML-driven decisions that personalise the entire commerce journey, from discovery through checkout and beyond. We operate at scale across hundreds of millions of customers, and we are expanding into new frontiers — combining the latest advances in agentic and generative AI, behavioural simulation, and causal inference to understand the impact of our decisions before they reach customers. We are looking for an Applied Scientist to join the Prime Video Commerce Insights team in London. You will develop and deploy customer-facing models, understand customer behaviour at scale, and explore emerging techniques that help us make better decisions faster. This is a delivery focused role within a high-visibility multidisciplinary group of engineers and scientists, focused on improving the customer experience for Prime Video. Key job responsibilities - Research, design, and implement machine learning approaches (e.g. reinforcement learning and recommendation systems) that personalise across different customer touch points. - Collaborate with engineers to deploy and integrate successful experiment results into large-scale, complex Amazon production systems with low latency. - Design and execute rigorous experiments to demonstrate the technical efficacy and business value of your methods. - Act as a subject-matter expert and help define the science roadmap and research agenda in line with organisational priorities and production constraints. - Provide machine learning thought leadership to technical and business leaders, thinking strategically about business, product, and technical challenges. - Work with technical product managers to work backwards from what matters to customers and deliver ML-backed solutions. - Share results with the team and wider scientific community through documents that are both statistically rigorous and compellingly relevant. A day in the life You will be a research leader and innovator within the Commerce Insights organisation. You will collaborate with talented engineers and senior leaders to solve problems that are uniquely challenging at Amazon's scale: personalising commerce decisions across multiple business lines, balancing competing objectives, and positively impacting hundreds of millions of customers worldwide. The problems here are technically deep — combining large-scale ML, causal reasoning, and behavioural modelling in a domain where every decision carries real revenue and customer-experience consequences. Your research will ship to production and move metrics that matter. About the team You will join a team of engineers and applied scientists with a proven track record of solving highly complex, ambiguous problems — work that has produced patents and publications at top-tier conferences. The team has direct visibility to senior Prime Video leadership and collaborates broadly across Commerce, Content, and Platform teams to shape how customers discover, subscribe to, and engage with video content. This is a team that operates at the intersection of rigorous research and real-world impact, where your ideas move from whiteboard to production for hundreds of millions of customers.
US, WA, Seattle
AWS is seeking a Data Scientist to join our Consumer Experience team. We're looking for someone who is curious about large-scale data challenges and motivated to apply ML/AI and advanced analytics to solve real customer problems. Reporting to the Science Lead, this role supports the analytical capabilities of AWS by applying emerging technologies, contributing to data science best practices, and partnering with stakeholders to deepen understanding of the AWS customer experience. The ideal candidate has experience working in complex data and analytics environments, with hands-on skills in Machine Learning and advanced analytics techniques — preferably within cloud computing. You should be comfortable building models and equally comfortable explaining what they mean to a non-technical audience. Key job responsibilities - Apply statistical analysis, ML, and complex data mining techniques to deliver insights that shape the AWS customer experience. - Build production-ready analytics solutions that support effective business decisions. - Partner with product, engineering, and design teams to develop and launch data products. - Contribute to the adoption of Gen AI and ML-based approaches across the data science practice, including building proof-of-concept AI-driven customer use cases. - Communicate technical findings clearly to both technical and non-technical stakeholders. - Bring new ideas — share approaches, tools, and methods that raise the bar for the team.
IN, KA, Bengaluru
Are you passionate about applying machine learning and advanced statistical techniques to protect one of the world's largest online marketplaces? Do you want to be at the forefront of developing innovative solutions that improve Amazon's customers experience? Do you thrive in a collaborative environment where diverse perspectives drive breakthrough solutions? If yes, we invite you to join the Amazon Customer Fulfillment & Prime analytics team. We're seeking an exceptional scientist who can revolutionize how we delight our customers. As a key member of our team, you'll develop and deploy machine learning systems that analyze millions of customer interactions daily, ensuring state of art experience for customers across 10 countries. Your work will directly impact the shopping experience for hundreds of millions of customers worldwide. Key job responsibilities • Ability to work independently across the end-to-end ML lifecycle: feature engineering, modeling, and MLOps to productionize models. • Strong foundation in machine learning and statistical modeling. • Experience deploying ML solutions into a production environment. • Apply machine learning and statistical techniques to create scalable abuse-detection solutions that identify fraudulent customer behavior, rings of accounts, identity change, holistic customer risk, and marketplace manipulation schemes. • Innovate with the latest GenAI technology to build highly automated solutions for efficient customer promotions. • Collaborate with cross-functional teams to develop comprehensive ML/statistical models that scale to millions of customers across 10+ countries. • Willing to travel to Mexico (MX) and Brazil (BR). • Comfortable working CET hours to maintain overlap with Mexico and Brazil business teams. About the team You'll be working closely with business partners, science and engineering teams to create end-to-end scalable machine learning solutions that address real-world problems. You will build scalable, efficient, and automated processes for large-scale data analyses, model development, model validation, and model implementation. You will also be providing clear and compelling reports for your solutions and contributing to the ongoing innovation and knowledge-sharing that are central to the team's success.
IN, KA, Bengaluru
Are you passionate about applying machine learning and advanced statistical techniques to protect one of the world's largest online marketplaces? Do you want to be at the forefront of developing innovative solutions that improve Amazon's customers experience? Do you thrive in a collaborative environment where diverse perspectives drive breakthrough solutions? If yes, we invite you to join the Amazon Customer Fulfillment & Prime analytics team. We're seeking an exceptional scientist who can revolutionize how we delight our customers. As a key member of our team, you'll develop and deploy machine learning systems that analyze millions of customer interactions daily, ensuring state of art experience for customers across 10 countries. Your work will directly impact the shopping experience for hundreds of millions of customers worldwide. Key job responsibilities • Ability to work independently across the end-to-end ML lifecycle: feature engineering, modeling, and MLOps to productionize models. • Strong foundation in machine learning and statistical modeling. • Experience deploying ML solutions into a production environment. • Apply machine learning and statistical techniques to create scalable abuse-detection solutions that identify fraudulent customer behavior, rings of accounts, identity change, holistic customer risk, and marketplace manipulation schemes. • Innovate with the latest GenAI technology to build highly automated solutions for efficient customer promotions. • Collaborate with cross-functional teams to develop comprehensive ML/statistical models that scale to millions of customers across 10+ countries. • Willing to travel to Mexico (MX) and Brazil (BR). • Comfortable working CET hours to maintain overlap with Mexico and Brazil business teams. About the team You'll be working closely with business partners, science and engineering teams to create end-to-end scalable machine learning solutions that address real-world problems. You will build scalable, efficient, and automated processes for large-scale data analyses, model development, model validation, and model implementation. You will also be providing clear and compelling reports for your solutions and contributing to the ongoing innovation and knowledge-sharing that are central to the team's success.
US, CA, Santa Monica
MULTIPLE POSITIONS AVAILABLE Employer: AMAZON.COM SERVICES LLC Offered Position: Applied Scientist III Job Location: Santa Monica, California Job Number: AMZ10564053 Position Responsibilities: Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications. Develop and/or apply statistical modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. Routinely build and deploy ML models on available data, and run and analyze experiments in a production environment. Identify new opportunities for research in order to meet business goals. Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists. 40 hours / week, 8:00am-5:00pm, Salary Range: $167,100/year to $226,100/year. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www.aboutamazon.com/workplace/employee-benefits. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.#0000
US, NY, New York
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! Demand Tech Experience (DTx), as an org, owns the Amazon Ads Console — the advertiser-facing workspace for creating and managing campaigns, reviewing performance, and acting on recommendations used by millions of advertisers. Our team, DTx Science, is the centralized science team within DTx, dedicated to improving and protecting the advertiser experience across ad consoles through applied science methodologies. The team drives impact through four core functions: Ad Console Personalization, Recommendation Development, Ad Console Experimentation, and DVA Agent Evaluation and Impact Measurement. We leverage a breadth of state-of-the-art techniques such as deep learning, reinforcement learning, LLMs, long term causal modeling as well as sophisticated A/B testing to develop personalized experiences with directly quantifiable business and advertiser success outcomes. We are looking for an accomplished machine learning expert to lead the Applied Science strategy for our recommendation creation and personalization program. In this role, you will work closely with business leaders, stakeholders and cross-functional teams to drive program success through ML-driven solutions. You will shape the applied science roadmap, promote a culture of data-driven decision-making, and deliver significant business impact for millions of advertisers worldwide and the company using advanced data techniques and applied science methodologies. Key job responsibilities As an Applied Scientist on this team, you will - Serve as the technical leader in Machine Learning, driving collaboration between scientists and engineers, guiding efforts within the team and collaborating with other teams. - Conduct hands-on analysis and modeling of large-scale data to generate insights that boost ads revenue while maintaining a positive advertiser and shopper experience. - Lead end-to-end Machine Learning projects that involve high levels of ambiguity, scale, and complexity. - Build, experiment, optimize, and deploy machine learning models, collaborating with software engineers to bring your models into production. - Run A/B experiments, gather data, and perform statistical analysis to validate your models. - Develop scalable and automated processes for large-scale data analysis, model development, validation, and serving. - Explore and research innovative machine learning approaches to push the boundaries of what’s possible. About the team The DTx Science team is the centralized science team within Demand Tech Experience (DTx), dedicated to improving and protecting the advertiser experience across ad consoles through applied science methodologies. The team drives impact through four core functions: Ad Console Personalization, Recommendation Development, Ad Console Experimentation, and DVA Agent Evaluation and Impact Measurement. Improve advertiser experience: Ad Console Personalization and Recommendation Development aim to improve the advertiser ad console experience by providing customized and personalized console experiences for each user and increasing their ad performance with relevant, science-backed onboarding and oppertunty recommendations. Protect advertiser experience: Ad Console Experimentation and DVA Agent Evaluation and Impact Measurement protect the advertiser experience by supporting the organization in making data-driven decisions to launch UX and agentic features that benefit advertisers.