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, NY, New York
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The 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! The Creative X team within Amazon Advertising time aims to democratize access to high-quality creatives (text, audio, images, videos) by building AI-driven solutions for advertisers. To accomplish this, we are investing in latent-diffusion models, large language models (LLM), generative audio (music and speech synthesis), computer vision (CV), reinforced learning (RL) and related methods. You will be part of a close-knit team of applied scientists and product managers who are highly collaborative and at the top of their respective fields. We are looking for talented Applied Scientists who have a proven record of developing Generative AI science at the highest standards of innovation, and experience working and delivering product-ready code, are adept at a variety of skills, especially with LLMs, generative audio, computer vision, latent diffusion or related foundational models that will accelerate our plans to generate high-quality creatives on behalf of advertisers. Every member of the team is expected to build customer (advertiser) facing features, contribute to the collaborative spirit within the team, publish, patent, and bring innovation research to raise the bar within the team.
US, NY, New York
Amazon Advertising is one of Amazon's fastest growing businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The 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! The Creative X team within Amazon Advertising time aims to democratize access to high-quality creatives (audio, images, videos, text) by building AI-driven solutions for advertisers. To accomplish this, we are investing in understanding how best users can leverage Generative AI methods such as latent-diffusion models, large language models (LLM), generative audio (music and speech synthesis), computer vision (CV), reinforced learning (RL) and related. As an Applied Scientist you will be part of a close-knit team of other applied scientists, engineers and product managers who are highly collaborative and at the top of their respective fields. We are looking for talented Applied Scientists who are adept at a variety of skills, especially at the interface of how users can use state-of-the-art generative music and audio, computer vision, latent diffusion or related foundational models that will accelerate our plans to generate high-quality creatives on behalf of advertisers. Every member of the team is expected to build customer (advertiser) facing features, contribute to the collaborative spirit within the team, publish, patent, and bring innovative research to raise the bar within the team. You will: - Drive the invention and development of novel methods for the use of Generative AI in ads - Work closely and integrate end-to-end proof-of-concept Machine Learning projects that have a high degree of ambiguity, scale and complexity. - Build interface-oriented systems that use Machine Learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your 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. - Mentor and help recruit Applied Scientists to the team. - Present results and explain methods to senior leadership. - Willingness to publish research at internal and external top scientific venues. - Write and pursue IP submissions. Key job responsibilities This role is focused on developing Machine Learning and Generative AI methods to augment generative imagery and videos. You will develop new paradigms that will impact how users can engage and benefit from GenAI and that are at the core of advertising-facing tools that we are launching. You will also work on development of ML and GenAI models. You will conduct literature reviews to stay on the top of the field. You will regularly engage with product managers, who will partner with you to productize your work. About the team
US, NY, New York
We are seeking an Applied Scientist to develop and optimize Visual Inertial Odometry (VIO) and sensor fusion systems for our intelligent robots. In this role, you will design, implement, and deploy state estimation and tracking algorithms that enable robots to understand their position and motion in real time, even in challenging and dynamic environments. You will own the full pipeline from algorithm development through embedded deployment, ensuring that perception systems run efficiently on resource-constrained robotic hardware. You will also leverage modern machine learning approaches to push the boundaries of classical perception methods, combining learned representations with geometric techniques to achieve robust, real-time performance. This is a deeply hands-on role. You will work directly with sensors, hardware, and real-world data, while prototyping, testing, and iterating in physical environments. The ideal candidate has strong foundations in VIO and sensor fusion, practical experience optimizing algorithms for embedded platforms, and familiarity with how modern deep learning is transforming perception. Key job responsibilities - Design and implement Visual Inertial Odometry algorithms for robust real-time state estimation on robotic platforms like Sprout - Develop multi-sensor fusion pipelines integrating cameras, IMUs, and other sensing modalities for accurate pose tracking - Optimize perception and tracking algorithms for deployment on embedded hardware (e.g., ARM, GPU-accelerated edge devices) under strict latency and power constraints - Apply modern ML-based perception techniques (learned features, depth estimation, neural odometry) to complement and improve classical geometric approaches - Build and maintain calibration, evaluation, and benchmarking infrastructure for perception systems - Collaborate with hardware, controls, and navigation teams to integrate perception outputs into the robot’s autonomy stack - Lead technical projects from research prototyping through production deployment
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, CA, San Diego
Can a large language model read a regulatory change and draft the requirements and control tests that follow from it, accurately enough for a Compliance Officer to sign off? How do you train a breach-risk model when confirmed breaches are rare, arrive months after the event, and mean different things to Compliance, Assurance, and the regulator? What does a model have to prove before a Compliance team acts on its output? We are looking for a Senior Applied Scientist to join the SPARC team within Risk and Compliance Solutions (RCS). SPARC's bold outcome is to accelerate the end-to-end regulatory change cycle by 10x, supercharging Compliance Officers as part of Amazon’s first AI-Native Second Line of Defense (2LoD). Our team builds the data, analytics, and modeling layer that RCS runs on, from regulatory reports and filings to the intelligence that tells Compliance Officers and our first line of defense (1LoD) partners where risk concentrates and which controls hold. You build the machine learning (ML) and generative artificial intelligence (GenAI) systems in that layer, take them into production, and own the evaluation science that lets Compliance rely on them. The work spans 3 areas: risk models that score which open risks and control weaknesses convert to breaches; GenAI systems that remove manual effort from requirement translation, control testing, and regulatory reporting, with human approval gates at every stage; and the evaluation science behind every model and agent the team ships. Financial crime compliance is the first domain, and its constraints shape the science: threats change faster than control sets adapt, and every output faces internal audit and external examination. Once an approach proves out, you carry it into the next compliance domain across the RCS portfolio. As a Senior Applied Scientist on SPARC, you own the science strategy for this layer, not just its individual models. You design and architect the agentic systems at the heart of it — objective-driven agents with human approval gates — and customize the technology to real compliance use cases. You define a multi-year science vision and roadmap for ML and GenAI in RCS, translate it into concrete plans for scientists and engineering partners, and anticipate where generative AI is heading so what you build capitalizes on compounding advances. You are the technical leader in AI/ML for the team and across partner teams, setting the standard for scientific rigor, raising the bar in design and model reviews, and mentoring scientists and engineers. You own problems from formulation to production: framing the science question with Compliance and 1LoD partners, designing experiments and backtests, building and validating models, and shipping them into the pipelines, reports, and tools that RCS teams use. The stack includes Amazon SageMaker, Amazon Bedrock, Amazon Redshift, and AWS Lambda, and your partners include data scientists, data engineers, business intelligence engineers, and software development engineers across RCS. The successful candidate treats an auditor's question as a design requirement, writes production-quality code alongside their models, and stays comfortable when the evaluation set does not exist until they build it. Key job responsibilities • Formulate ambiguous compliance problems as ML and GenAI problems with Compliance and 1LoD partners, and choose methods that fit the data, the risk, and the audit standard • Develop risk models that learn from rare, delayed, and noisy labels to score which risks and control weaknesses convert to breaches, and calibrate them so a score carries a defensible meaning • Build GenAI systems that remove manual effort from requirement translation, control testing, and regulatory reporting, with human approval gates at every stage • Design the evaluation for every ML and GenAI system you ship: golden sets that compliance experts label, metrics suited to rare outcomes and generated text, and release criteria a system meets before Compliance relies on it • Deploy and monitor models in production with software development engineers, including drift detection, performance tracking against realized outcomes, and retraining criteria • Explain model decisions, quantify uncertainty, and document methodology so Compliance Officers, auditors, and examiners can trace how a system reached each output • Create reusable science components, such as feature sets, scoring services, and evaluation harnesses, so an approach that works in financial crime compliance extends to the next domain without a rebuild • Design and architect the pod's agentic systems and customize them to compliance use cases, working toward 10x acceleration of the end-to-end regulatory change cycle while maintaining or improving quality • Set the technical direction for the pod's science: lead complex model and design reviews across teams, define evaluation methods and release standards others adopt, mentor data scientists and engineers on ML methods and experimental design, and publish or patent where the work and confidentiality allow • Define a long-term science vision for RCS compliance AI driven from Compliance and 1LoD needs, translate it into actionable plans for science, engineering, and product partners, and influence where the science impacts the portfolio next About the team Risk and Compliance Solutions (RCS) serves as a crucial safeguard for Amazon's buyers, brands, and selling partners while ensuring business teams meet their regulatory obligations. RCS operates as the second line of defense under the Three Lines of Defense (3LoD) model, providing specialized oversight, monitoring, and expertise while setting policies and procedures that guide Amazon's compliance framework. RCS's mission is to apply specialist industry insights and Amazon's unique approach to scale through technology, delighting customers through tailored compliance solutions. Payment regulatory compliance keeps the financial system closed to bad actors while widening access for hundreds of millions of good customers, and protects the licenses behind roughly $650B in annual activity across 18 entities and 45 regulated products in 6 regions.
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.
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, 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.