PhD students from Amazon's first class of remote interns: Alesia Chernikova, Meghana Palukuri, Zihao Wang, Kai Xiao, Lisa Yu
From left to right: Alesia Chernikova, Meghana Palukuri, Zihao Wang, Kai Xiao, and Lisa Yu. These five PhD students were among Amazon's first class of remote interns.
Glynis Condon

2020 science interns discuss what it’s like to intern virtually

Learn how these five PhD students used technology to stay connected, and get the most out of a unique internship experience.

This year, Amazon hosted more than 8,000 interns across the globe. That figure is significant for two reasons: First, it’s the largest class of interns in company history. Second, for the vast majority of interns this year, their entire internship was virtual. We asked five interns what it was like to intern remotely, and to share how that shaped their experiences.

Below they talk about what it’s like to be an intern during a global pandemic, the vital role of technology in ensuring their experiences were enriching, and the advice they would give to future interns.

As a science intern, what excites you about the future of your field after your internship? What is the most valuable experience or learning you take away from your internship? 

Zihao Wang, Emory University, PhD student in computer science and applied scientist intern: The application of deep learning on spoken language understanding will continue to have a critical impact on improving satisfaction of users in conversations with conversational agents. This is important because conversational agents are used in many fields right now and will be used in more and more fields to affect people’s everyday lives. The most valuable experience is that in the real life applications, we not only need to work on common problems, but also on long-tail problems, and in many cases, it’s the long-tail problem that will impact tremendously on user experience.

Meghana Palukuri, The University of Texas at Austin, PhD student in computational science, engineering and mathematics and applied scientist intern: My internship was the first opportunity I had to dive deeper into the field of natural language processing. The impact that can be created by the field is inspiring, as a lot of data is available in the textual form and analyzing it can yield powerful and useful algorithms. For instance, in my internship project, I built a product embedding space for making substitute product recommendations. I am excited about how the performance of models like these can be improved by advances in the field with better text representations (sentence embeddings). The most valuable learning from my internship is to never stop learning, for example, by spending time reading state-of-the-art research papers. 

Alesia Chernikova, Northeastern University, PhD student in computer science and applied scientist intern: During the internship, I was excited to work in the field of scientific research, which currently is in great demand in both academia and industry, and which has the prerequisites for further improvement and development. While working on the project, I was happy to have the opportunity to develop a new methodology to solve the existing problem, and put it into practice on real data. Last but not least, I learned how to dive deeply into the problem and look at it from different perspectives, taking into account the already existing solutions.

What was the single most useful tool you used during your virtual internship?

Lisa Yu, The George Washington University, PhD student in statistics and data science intern: For my home-office set-up, the 32-inch 4K monitor provided by Amazon was extremely useful! I enjoy it almost too much.

Kai Xiao, North Carolina State University, PhD student in computer science and applied scientist intern: I would say definitely the wide monitor. I could put so much stuff on it yet was still able to effectively find what I needed. This is crucial to tech roles, especially when you have to keep multiple terminals open for reading code, which would normally require scrolling up and down with a regular sized monitor. One other thing is subscribing to the research mailing lists. When I had technical questions that I couldn’t find answers for, sending questions to the broader mailing list always helped. There’s always someone subscribed to the list that can help with the aspect you’re not familiar with and it also served as a  good resource to find mentors.

Alesia Chernikova: We used a whiteboard application that was very helpful when I discussed the theoretical part of my project, such as mathematical formulas, algorithms, and coding techniques. We also used it during our research group meetings when someone presented new information to other people in the team. In addition, the Chime calling feature was really helpful. Whenever I needed help or clarification from my colleagues, I could easily call or message them to get the answer to my question.

Meghana Palukuri: As an intern who had not met anyone on my team before joining, technology that connects people was essential for work,  for developing interpersonal relationships ,and for providing support during these times, when a lot of us are isolated at our homes. Sometimes, we would be on a call together while working, just to give us the feeling of being in the same office space.

Zihao Wang: Although COVID-19 prevented us from meeting in person, the technology enabled us to interact with each other pretty closely. Chime, Slack, Quip, and other online docs, as a united suite of technology tools, helped me get onboarded, acquire essential knowledge, communicate with teammates, network, and make progress. Through these tools, I felt very warmly welcomed, and strongly supported by my teammates.

Which events did you find the most helpful?

Kai Xiao: The amount of exposure to new knowledge was a big bonus interning at Amazon. I constantly looked for things in our internal posters site (since we didn’t have access to company elevators), and most of the experiences were positive and engaging. Much of my fulfillment came from finally having a place to utilize my communication skills within these events. Being virtual means you lose most of the interaction, and having these events really went a long way in maintaining a certain level of engagement between me and the company. I was always excited when finding some new events to attend.

Meghana Palukuri: The Science Intern Cohort Program gave me the opportunity to connect with fellow PhD students working on very interesting research problems. Putting together a poster for the Graduate Research Poster session felt great, and also helped me prepare for my final presentation. The Alexa Skills Hackathon was also really fun. I worked with four other interns to build my first Alexa skill – ‘intern chat’ to enhance the pre-onboarding experience for future interns. I took part in the three-day MLA-NLP (machine learning accelerator – natural language processing) workshop, attended by both interns and full-time employees. The final project, on classification of customer product reviews, was a great learning experience.

Alesia Chernikova: I attended the Science Cohort Program, speaker series/intern panel, and poster session. All of these student events helped me to learn more about Amazon, the variety of teams and projects, and internship-related questions. All these activities were especially helpful in virtual environment settings. For instance, by virtue of the Science Cohort Session, I built connections with other interns, listened to their experiences during the internship, and learned about the research projects they were working on both at university and Amazon. It was beneficial for me to look at things not only from the inside, but also understand it from the perspective of others.

What is one piece of advice you would give to future interns?

How to apply

Amazon’s Graduate Research internship program includes mentorship, moderated discussion groups, opportunities to connect with fellow interns, fireside chats with senior leaders, and a variety of networking events.

If you’re a student with interest in an Amazon internship, you can find additional information here, and submit your details for review. Students can also learn more about internship opportunities at  Amazon Student Programs.

Lisa Yu: For future interns, if they are doing virtual internships, the most important thing I want to mention is communication! I suggest participating in team hang-outs to interact with and become familiar with their team members. Also, attend intern events to communicate with other interns in order not to feel alone during a virtual internship.

Kai Xiao: Communication is the key – especially with stakeholders. These people are normally your direct reports, mentors, and team members, but most importantly your customers! A good way to avoid anxiety is to plan your day, especially in a virtual setup. Every morning I would pull out my calendar, “time box” certain blocks of the day to be work time. It is perfectly OK if some of the time boxes are leisure times, as long as that’s in your plan. This method saved my virtual internship this year.

Zihao Wang: I would say to future interns that it’s never too early to start preparing yourself for new internship/job opportunities. Start acquiring  as much knowledge as you can that’s relevant to your research interest, such as domain knowledge, usage of tools, and even communication skills. You will find yourself in situations where you feel you should have honed your skills before, or where you actually feel lucky that you acquired that skill during  your spare time.

Related content

GB, London
We are looking for a Senior Economist to work on exciting and challenging business problems related to Amazon Retail’s worldwide product assortment. You will build innovative solutions based on econometrics, machine learning, and experimentation. You will be part of a interdisciplinary team of economists, product managers, engineers, and scientists, and your work will influence finance and business decisions affecting Amazon’s vast product assortment globally. If you have an entrepreneurial spirit, you know how to deliver results fast, and you have a deeply quantitative, highly innovative approach to solving problems, and long for the opportunity to build pioneering solutions to challenging problems, we want to talk to you. Key job responsibilities * Work on a challenging problem that has the potential to significantly impact Amazon’s business position * Develop econometric models and experiments to measure the customer and financial impact of Amazon’s product assortment * Collaborate with other scientists at Amazon to deliver measurable progress and change * Influence business leaders based on empirical findings
IN, KA, Bengaluru
Alexa+ is Amazon’s next-generation, AI-powered virtual assistant. Building on the original Alexa, it uses generative AI to deliver a more conversational, personalised, and effective experience. Alexa Sensitive Content Intelligence (ASCI) team is developing responsible AI (RAI) solutions for Alexa+, empowering it to provide useful information responsibly. The Mission Build AI safety systems that protect millions of Alexa customers every day. As conversational AI evolves, you'll solve challenging problems in Responsible AI by ensuring LLMs provide safe, trustworthy responses, building AI systems that understand nuanced human values across cultures, and maintaining customer trust at scale. We are looking for a passionate, talented, and inventive Data Scientist-II to help build industry-leading technology with Large Language Models (LLMs) and multimodal systems, requiring good learning and generative models knowledge. You will be working with a team of exceptional Data Scientists working in a hybrid, fast-paced organization where scientists, engineers, and product managers work together to build customer facing experiences. You will collaborate with other data scientists while understanding the role data plays in developing data sets and exemplars that meet customer needs. You will analyze and automate processes for collecting and annotating LLM inputs and outputs to assess data quality and measurement. You will apply state-of-the-art Generative AI techniques to analyze how well our data represents human language and run experiments to gauge downstream interactions. You will work collaboratively with other data scientists and applied scientists to design and implement principled strategies for data optimization. Key job responsibilities A Data Scientist-II should have a reasonably good understanding of NLP models (e.g. LSTM, LLMs, other transformer based models) or CV models (e.g. CNN, AlexNet, ResNet, GANs, ViT) and know of ways to improve their performance using data. You leverage your technical expertise in improving and extending existing models. Your work will directly impact our customers in the form of products and services that make use of speech, language, and computer vision technologies. You will be joining a select group of people making history producing one of the most highly rated products in Amazon's history, so if you are looking for a challenging and innovative role where you can solve important problems while growing in your career, this may be the place for you. A day in the life You will be working with a group of talented scientists on running experiments to test scientific proposal/solutions to improve our sensitive contents detection and mitigation for worldwide coverage. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, policy, model development, and solution implementation. You will work with other scientists, collaborating and contributing to extending and improving solutions for the team. About the team Our team pioneers Responsible AI for conversational assistants. We ensure Alexa delivers safe, trustworthy experiences across all devices, modalities, and languages worldwide. We work on frontier AI safety challenges—and we're looking for scientists who want to help shape the future of trustworthy AI.
IN, KA, Bengaluru
Alexa+ is Amazon’s next-generation, AI-powered virtual assistant. Building on the original Alexa, it uses generative AI to deliver a more conversational, personalised, and effective experience. Alexa Sensitive Content Intelligence (ASCI) team is developing responsible AI (RAI) solutions for Alexa+, empowering it to provide useful information responsibly. The Mission Build AI safety systems that protect millions of Alexa customers every day. As conversational AI evolves, you'll solve challenging problems in Responsible AI by ensuring LLMs provide safe, trustworthy responses, building AI systems that understand nuanced human values across cultures, and maintaining customer trust at scale. We are looking for a passionate, talented, and inventive Data Scientist-II to help build industry-leading technology with Large Language Models (LLMs) and multimodal systems, requiring good learning and generative models knowledge. You will be working with a team of exceptional Data Scientists working in a hybrid, fast-paced organization where scientists, engineers, and product managers work together to build customer facing experiences. You will collaborate with other data scientists while understanding the role data plays in developing data sets and exemplars that meet customer needs. You will analyze and automate processes for collecting and annotating LLM inputs and outputs to assess data quality and measurement. You will apply state-of-the-art Generative AI techniques to analyze how well our data represents human language and run experiments to gauge downstream interactions. You will work collaboratively with other data scientists and applied scientists to design and implement principled strategies for data optimization. Key job responsibilities A Data Scientist-II should have a reasonably good understanding of NLP models (e.g. LSTM, LLMs, other transformer based models) or CV models (e.g. CNN, AlexNet, ResNet, GANs, ViT) and know of ways to improve their performance using data. You leverage your technical expertise in improving and extending existing models. Your work will directly impact our customers in the form of products and services that make use of speech, language, and computer vision technologies. You will be joining a select group of people making history producing one of the most highly rated products in Amazon's history, so if you are looking for a challenging and innovative role where you can solve important problems while growing in your career, this may be the place for you. A day in the life You will be working with a group of talented scientists on running experiments to test scientific proposal/solutions to improve our sensitive contents detection and mitigation for worldwide coverage. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, policy, model development, and solution implementation. You will work with other scientists, collaborating and contributing to extending and improving solutions for the team. About the team Our team pioneers Responsible AI for conversational assistants. We ensure Alexa delivers safe, trustworthy experiences across all devices, modalities, and languages worldwide. We work on frontier AI safety challenges—and we're looking for scientists who want to help shape the future of trustworthy AI.
EG, Cairo
Are you a MS or PhD student interested in a 2026 internship in the field of machine learning, deep learning, generative AI, large language models and speech technology, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods? If so, we want to hear from you! We are looking for students interested in using a variety of domain expertise to invent, design and implement state-of-the-art solutions for never-before-solved problems. You can find more information about the Amazon Science community as well as our interview process via the links below; https://www.amazon.science/ https://amazon.jobs/content/en/career-programs/university/science https://amazon.jobs/content/en/how-we-hire/university-roles/applied-science Key job responsibilities As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to write technical white papers, create roadmaps and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists and other science interns to develop solutions and deploy them into production. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon’s customer focused culture. The ideal intern must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. A day in the life At Amazon, you will grow into the high impact person you know you’re ready to be. Every day will be filled with developing new skills and achieving personal growth. How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow. Some more benefits of an Amazon Science internship include; • All of our internships offer a competitive stipend/salary • Interns are paired with an experienced manager and mentor(s) • Interns receive invitations to different events such as intern program initiatives or site events • Interns can build their professional and personal network with other Amazon Scientists • Interns can potentially publish work at top tier conferences each year About the team Applicants will be reviewed on a rolling basis and are assigned to teams aligned with their research interests and experience prior to interviews. Start dates are available throughout the year and durations can vary in length from 3-6 months for full time internships. This role may available across multiple locations in the EMEA region (Austria, Estonia, France, Germany, Ireland, Israel, Italy, Jordan, Luxembourg, Netherlands, Poland, Romania, Spain, South Africa, UAE, and UK). Please note these are not remote internships.
US, CA, San Diego
We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply their macroeconomics and forecasting skillsets to solve real world problems. The intern will work in the area of forecasting, developing models to improve the success of new product launches in Private Brands. Our PhD Economist Internship Program offers hands-on experience in applied economics, supported by mentorship, structured feedback, and professional development. Interns work on real business and research problems, building skills that prepare them for full-time economist roles at Amazon and beyond. You will learn how to build data sets and perform applied econometric analysis collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis About the team The Amazon Private Brands Intelligence team applies Machine Learning, Statistics and Econometrics/economics to solve high-impact business problems, develop prototypes for Amazon-scale science solutions, and optimize key business functions of Amazon Private Brands and other Amazon orgs. We are an interdisciplinary team, using science and technology and leveraging the strengths of engineers and scientists to build solutions for some of the toughest business problems at Amazon, covering areas such as pricing, discovery, negotiation, forecasting, supply chain and product selection/development.
US, WA, Seattle
Come be a part of a rapidly expanding $35 billion-dollar global business. At Amazon Business, a fast-growing startup passionate about building solutions, we set out every day to innovate and disrupt the status quo. We stand at the intersection of tech & retail in the B2B space developing innovative purchasing and procurement solutions to help businesses and organizations thrive. At Amazon Business, we strive to be the most recognized and preferred strategic partner for smart business buying. Bring your insight, imagination and a healthy disregard for the impossible. Join us in building and celebrating the value of Amazon Business to buyers and sellers of all sizes and industries. Unlock your career potential. Amazon Business Data Insights and Analytics team is looking for a Data Scientist to lead the research and thought leadership to drive our data and insights strategy for Amazon Business. This role is central in shaping the definition and execution of the long-term strategy for Amazon Business. You will be responsible for researching, experimenting and analyzing predictive and optimization models, designing and implementing advanced detection systems that analyze customer behavior at registration and throughout their journey. You will work on ambiguous and complex business and research science problems with large opportunities. You'll leverage diverse data signals including customer profiles, purchase patterns, and network associations to identify potential abuse and fraudulent activities. You are an analytical individual who is comfortable working with cross-functional teams and systems, working with state-of-the-art machine learning techniques and AWS services to build robust models that can effectively distinguish between legitimate business activities and suspicious behavior patterns You must be a self-starter and be able to learn on the go. Excellent written and verbal communication skills are required as you will work very closely with diverse teams. Key job responsibilities - Interact with business and software teams to understand their business requirements and operational processes - Frame business problems into scalable solutions - Adapt existing and invent new techniques for solutions - Gather data required for analysis and model building - Create and track accuracy and performance metrics - Prototype models by using high-level modeling languages such as R or in software languages such as Python. - Familiarity with transforming prototypes to production is preferred. - Create, enhance, and maintain technical documentation
US, CA, Pasadena
The Amazon Center for Quantum Computing in Pasadena, CA, is looking to hire an Applied Science intern who will specialize in hardware signal train design for quantum computing. Working alongside other scientists and engineers, you will design and validate hardware performing the control and readout functions for Amazon quantum processors, from room to cryogenic temperatures. Candidates must have a solid background in analog or mixed-signal design at the PCB level. Working effectively within a cross-functional team environment is critical. Key job responsibilities Our scientists and engineers collaborate across diverse teams and projects to offer state of the art, cost effective solutions for the control of Amazon quantum processor systems. You’ll bring a passion for innovation and collaboration to: Design cryogenic and room temperature printed circuit board based hardware, used for signal conditioning and control functions. Develop tests to validate hardware with both benchtop and cryogenic test setups with quantum devices. Explore enabling control technologies necessary for Amazon to produce commercially viable quantum computers. About the team Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Inclusive Team Culture Here at Amazon, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship and Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
US, VA, Arlington
About Sponsored Products and Brands The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through 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. About our team The SPB Offsite team builds solutions to extend campaigns to reach customers off the store and extend shopping experiences on third party sites where shoppers search and discover products. We use industry leading machine learning, high scale low latency systems, and AI technologies to create better sponsored customer experiences off the store. This role will have deep interest in building the next innovations in ad tech and shopping wherever shoppers go. You will work with external and internal partners to connect ad tech systems, understand customers, and drive results at scale. You are a deeply technical leader who operates with a GenAI first approach to product, engineering, and science based solutions. As an Applied Scientist on this team, you will: - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. - 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. - Build 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. - Research new and innovative machine learning approaches. 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.
US, WA, Seattle
Are you passionate about leveraging data and economics to enhance customer experience across Amazon's diverse businesses? The Customer Experience and Business Trends (CXBT) organization is seeking an Economist to join our Benchmarking Economics Analytics and Measurement (BEAM) team. Our mission is to drive customer experience improvements through innovative economic modeling, advanced analytics, and scalable scientific solutions. As an Economist on our team, you will collaborate with senior management, business stakeholders, scientists, engineers, and economics leadership to solve complex business challenges across Amazon's business lines. You'll develop sophisticated econometric models using our world-class data systems, applying diverse methodologies spanning causal inference, machine learning, and generative AI. In this fast-paced environment, you'll tackle challenging problems that directly influence strategic decision-making and drive measurable business impact. Key job responsibilities - Develop economic theory and deliver causal machine learning models at scale - Collaborate with cross-functional teams to translate research into scalable solutions - Write effective business narratives and scientific papers to communicate to both business and technical audiences - Drive data-driven decision making to improve customer experience About the team Customer Experience and Business Trends (CXBT) is an organization made up of a diverse suite of functions dedicated to deeply understanding and improving customer experience, globally. We are a team of builders that develop products, services, ideas, and various ways of leveraging data to influence product and service offerings – for almost every business at Amazon – for every customer (e.g., consumers, developers, sellers/brands, employees, investors, streamers, gamers). Our approach is based on determining the customer need, along with problem solving, and we work backwards from there. We use technical and non-technical approaches and stay aware of industry and business trends. We are a global team, made up of a diverse set of profiles, skills, and backgrounds – including: Product Managers, Software Developers, Computer Vision experts, Solutions Architects, Data Scientists, Business Intelligence Engineers, Business Analysts, Risk Managers, and more.
US, WA, Seattle
Are you passionate about leveraging data and economics to enhance customer experience across Amazon's diverse businesses? The Customer Experience and Business Trends (CXBT) organization is seeking an Economist to join our Benchmarking Economics Analytics and Measurement (BEAM) team. Our mission is to drive customer experience improvements through innovative economic modeling, advanced analytics, and scalable scientific solutions. As an Economist on our team, you will collaborate with senior management, business stakeholders, scientists, engineers, and economics leadership to solve complex business challenges across Amazon's business lines. You'll develop sophisticated econometric models using our world-class data systems, applying diverse methodologies spanning causal inference, machine learning, and generative AI. In this fast-paced environment, you'll tackle challenging problems that directly influence strategic decision-making and drive measurable business impact. Key job responsibilities - Develop economic theory and deliver causal machine learning models at scale - Collaborate with cross-functional teams to translate research into scalable solutions - Write effective business narratives and scientific papers to communicate to both business and technical audiences - Drive data-driven decision making to improve customer experience About the team Customer Experience and Business Trends (CXBT) is an organization made up of a diverse suite of functions dedicated to deeply understanding and improving customer experience, globally. We are a team of builders that develop products, services, ideas, and various ways of leveraging data to influence product and service offerings – for almost every business at Amazon – for every customer (e.g., consumers, developers, sellers/brands, employees, investors, streamers, gamers). Our approach is based on determining the customer need, along with problem solving, and we work backwards from there. We use technical and non-technical approaches and stay aware of industry and business trends. We are a global team, made up of a diverse set of profiles, skills, and backgrounds – including: Product Managers, Software Developers, Computer Vision experts, Solutions Architects, Data Scientists, Business Intelligence Engineers, Business Analysts, Risk Managers, and more.