A graphic shows a simulation of what a VR guided experience might look like, it features colored circles, a humanoid face, and other features
TRIPP is an Alexa Fund portfolio company that is exploring how virtual reality can be combined with meditation. The company's CEO and co-founder Nanea Reeves noted that the VR experiences "are deliberately psychedelic. You find yourself inside an atom or floating in space."
TRIPP

TRIPP explores the potential of virtual reality–powered meditation

Alexa Fund portfolio company’s science-led program could change how we approach mental wellness — and how we use VR.

(Editor’s note: This article is the latest installment in a series by Amazon Science delving into the science behind products and services of companies in which Amazon has invested. The Alexa Fund participated in TRIPP’s $11.2M Series A extension funding round in June 2022.)

With meditation soaring in popularity and the virtual reality (VR) industry booming, Alexa Fund portfolio company TRIPP is at the confluence of two powerful trends: mental well-being and VR. TRIPP is a digital wellness program that uses VR headsets to immerse users in breathing meditation experiences.

The idea to meld meditation and VR first occurred to TRIPP CEO and co-founder Nanea Reeves in 2017 when she, a lifelong practitioner of meditation with a 15-year career in the gaming industry, was experimenting with the medium by building a solitaire game in VR.

This graphic shows a potential visualization from the VR app TRIPP, it includes a planet floating in space against a background featuring stars and bright colors
TRIPP CEO Nanea Reeves said she was inspired by the work of Giuseppe Riva, a neuropsychologist. “We wondered if we could create environments that make you go, ‘Oh, wow!’ and give you a lift,” Reeves explains.
TRIPP

“The way I felt exploring VR was even more interesting to me than the actual development,” Reeves says. Her interest developed into a deep curiosity about the psychological effects of VR, and she began searching the scientific literature.

In addition to studying VR in medical and mental health use cases, she discovered work by Giuseppe Riva, a neuropsychologist whose research has shown that VR can elicit emotions such as awe and, in turn, influence people’s well-being, agency, and perceptions of themselves.

“Inspired by Giuseppe’s research, we wondered if we could create environments that make you go, ‘Oh, wow!’ and give you a lift,” Reeves explains. That became her impetus to found TRIPP in 2017, pursuing the hypothesis that, by stimulating experiences through VR, people may gain some agency over their emotions.

Riva’s work identified several aspects of VR that made it particularly effective for evoking awe, including its immersive nature and the complexity and scale of virtual environments.

“We started leaning into that, and we started to play with scale in our designs,” says Reeves.

In 2019, TRIPP launched its award-winning wellness application, TRIPP, in VR. The application offers immersive mindfulness experiences and, to date, has delivered nearly 6 million wellness sessions. TRIPP continues to work closely with neuroscience and psychiatry advisors through PsyAssist to design and evaluate their experiences and with a host of researchers who are studying its potential uses.

A recent clinical trial suggested that TRIPP might positively influence well-being and mood in cancer patients, and ongoing projects are assessing whether TRIPP can help people in recovery from substance use disorders or anxiety and pain control, among other initiatives.

“With some of the early data coming in, it seems very promising that tools like TRIPP might have a positive impact,” Reeves says, “but we are still only at the beginning of what may be possible with VR.”

Amazon Science spoke with Reeves about the motivation for TRIPP, its roots in science, and the implications for what it can achieve with VR.

  1. Q. 

    Why take meditation virtual?

    A. 

    It’s actually a super native case for VR, because the immersive quality allows you to unplug. You can’t look at your phone by nature of the immersion. I was blown away by how I felt moving in and out of VR — the feeling of respite.

    A lot of the early VR experiences simulated environments that made you terrified, like walking a plank or standing at the edge of a cliff. And it occurred to me: if we could scare people so easily, could we trigger other emotional changes that are beneficial?

    Our approach is to use immersion to drive a deeper connection to self-contemplative thoughts. You’re immersed in this psychologically safe container that is designed to capture your awareness, to allow you to be present and connect to self. With VR, it’s not just an audio file guiding you toward connecting with your breath. We can show you your breath, like star crystals coming in and out of your mouth.

    Some of the early offerings thought VR was really only for gaming. When we first got TRIPP on Oculus, they didn’t know where to put us because they didn’t have a relaxation genre then. We were pretty buried in the store. But we started to get a little bit of traction, and we soon had surprisingly regular usage over time. VR has this problem where you go in, you go, “Wow, that was amazing!” and then it's in your closet. You never pick it up again. When we were designing the product, we knew we had to build for repeat usage. So, we built it procedurally, and now we can update it from the server and add new content regularly.

  2. Q. 

    How is science leading the design and development of TRIPP?

    A. 

    I started by looking at the research investigating VR’s effect on the brain, largely by neuroscientists and behavioral therapists exploring mental health and medical use cases for VR. Most of them focused on simulation, like simulated exposure therapy. But I wondered if, instead of simulating something, could we stimulate responses? I took that question to the researchers working on VR and its effects on mental well-being. We started digging into the research and then, based on the research data, designed VR experiences intended to trigger states of wonder and awe. We tried them out on people and captured some physiological data like heart rate and EEG to see if the experiences were directionally achieving the effect we wanted.

    We stay very grounded in research-driven design choices. We’re a bit edgy. Rather than mimicking natural environments, the experiences are deliberately psychedelic. You find yourself inside an atom or floating in space. First, we tried things like a waterfall or a beach, but when we tested them, they didn’t feel good. I found some research describing how sensory dissonance in synthetic natural environments can create a stress response. Your brain goes, “Well, it looks like a beach, but I don’t smell the ocean. So what’s wrong with this environment?” We realized we had to create environments for which you have no mental model. So we said, “OK, let’s put you in a cosmic flotation tank, whatever that means, because no one knows what space smells like.”

    We’re also starting an enterprise program to support employee wellness and team-building with a hybrid workforce, but also with a focus on using the metaverse for driving ideation and innovation. Can we use these otherworldly environments to spark creativity?
    Nanea Reeves

    After we launched, we started collecting data on mood and emotional state in the live user sessions via self-reported surveys that are based on what they use in mental health research. We bookended our sessions with users, basically asking “How do you feel?” before and after each session. We did things like randomizing the order of the response selections to control against position bias. Now, we have data collected from close to 6 million sessions that we can slice and dice by the time of day and, for a percentage of our audience who opted in, age, gender, and location. It’s become a meaningful body of data that we can share with researchers once it has been de-identified. We also work with researchers who want to study TRIPP and its potential applications. It’s been fascinating to work with that community.

    One example is this group in Germany working with cancer patients undergoing surgery, looking at the effects of TRIPP sessions on their quality of life, well-being, and mood. This study was published in Nature’s Scientific Reports. Participation was good, and patients who used TRIPP had lower heart rates and breathing rates after their sessions. They had improved scores on their mood and emotion surveys after the sessions too. What the study shows us is that VR-based relaxation is a viable option and may be beneficial for cancer patients undergoing surgery. Of course, we don’t make any therapeutic claims until we have a tremendous amount of evidence to support those claims.

    You can find other published data and scientific reports examining TRIPP’s effects on adolescents and its use in palliative care. And we’re working with researchers who are looking at whether TRIPP could help people experiencing addiction and rehab, chemotherapy, severe mental illness, anxiety, and pain. Researchers are also using TRIPP to ease anxiety and help people prepare for ketamine-assisted therapy, so they get the most out of their treatment. I feel very motivated to see how we can help and participate in these research initiatives.

  3. Q. 

    How might TRIPP change how we use VR, beyond its medical applications?

    A. 

    Earlier this year, we acquired EvolVR, which holds live group meditations. Several hundred avatars attend the most popular conversations. People really open up. Skip Rizzo, PhD, a renowned researcher in the field and an advisor to TRIPP, did a pilot study and found that people suffering from PTSD were more open and honest with an avatar. We want to further investigate this as there’s something about the “digital veil” of VR where you don’t feel the judgment of being seen by other people. I think this is a wonderful use case for the metaverse.

    We’re also starting an enterprise program to support employee wellness and team-building with a hybrid workforce, but also with a focus on using the metaverse for driving ideation and innovation. Can we use these otherworldly environments to spark creativity?

    It’s also fascinating to think about the gig economy that could emerge from the metaverse — similar to what first emerged from mobile computing. For example, I met a woman at one of our live group meditation events in the metaverse who’s earning a living as one of the top world-builders in Altspace VR. She’s a mother of five who has never worked in tech before. She’s now a programmer, building these virtual worlds.

    We’re only beginning to explore the potential of VR. It’s like the early days of mobile. Initially, no one thought we’d want to play games or even text message on our cell phones. Now, for the past decade, we have been walking around with our heads down staring at these phone screens nonstop. What kind of innovation will happen in a future when XR glasses are ubiquitous and allow us to experience the world around us in an entirely new and adaptive way?

Related content

  • Staff writer
    December 29, 2025
    From foundation model safety frameworks and formal verification at cloud scale to advanced robotics and multimodal AI reasoning, these are the most viewed publications from Amazon scientists and collaborators in 2025.
  • Staff writer
    December 29, 2025
    From quantum computing breakthroughs and foundation models for robotics to the evolution of Amazon Aurora and advances in agentic AI, these are the posts that captured readers' attention in 2025.
  • Staff writer
    February 4, 2026
    An early meeting between Amazon scientists and Stanford researchers led to cvc5, an open-source tool now powering approximately one billion automated-reasoning checks across AWS every day.
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.
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.
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, 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, MA, Boston
MULTIPLE POSITIONS AVAILABLE Employer: AMAZON WEB SERVICES, INC. Offered Position: Data Scientist III Job Location: Boston, Massachusetts Job Number: AMZ9674163 Position Responsibilities: Own the data science elements of various products to help with data-based decision making, product performance optimization, and product performance tracking. Work directly with product managers to help drive the design of the product. Work with Technical Product Managers to help drive the build planning. Translate business problems and products into data requirements and metrics. Initiate the design, development, and implementation of scientific analysis projects or deliverables. Own the analysis, modelling, system design, and development of data science solutions for products. Write documents and make presentations that explain model/analysis results to the business. Bridge the degree of uncertainty in both problem definition and data scientific solution approaches. Build consensus on data, metrics, and analysis to drive business and system strategy. Position Requirements: Master's degree or foreign equivalent degree in Statistics, Applied Mathematics, Economics, Engineering, Computer Science or a related field and two years of experience in the job offered or a related occupation. Employer will accept a Bachelor's degree or foreign equivalent degree in Statistics, Applied Mathematics, Economics, Engineering, Computer Science, or a related field and five years of progressive post-baccalaureate experience in the job offered or a related occupation as equivalent to the Master's degree and two years of experience. Must have one year of experience in the following skills: (1) building statistical models and machine learning models using large datasets from multiple resources; (2) building complex data analyses by leveraging scripting languages including Python, Java, or related scripting language; and (3) communicating with users, technical teams, and management to collect requirements, evaluate alternatives, and develop processes and tools to support the organization. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation. 40 hours / week, 8:00am-5:00pm, Salary Range $161,803/year to $215,300/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.#0000
US, CA, Palo Alto
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading 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. Amazon Ads Response Prediction team is your choice, if you want to join a highly motivated, collaborative, and fun-loving team with a strong entrepreneurial spirit and bias for action. We are seeking an experienced and motivated Machine Learning Applied Scientist who loves to innovate at the intersection of customer experience, deep learning, and high-scale machine-learning systems. Amazon Advertising operates at the intersection of eCommerce and advertising, and is investing heavily in building a world-class advertising business. We are defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products to improve both shopper and advertiser experience. With a broad mandate to experiment and innovate, we grow at an unprecedented rate with a seemingly endless range of new opportunities. We are looking for a talented Machine Learning Applied Scientist for our Amazon Ads Response Prediction team to grow the business. We are providing advanced real-time machine learning services to connect shoppers with right ads on all platforms and surfaces worldwide. Through the deep understanding of both shoppers and products, we help shoppers discover new products they love, be the most efficient way for advertisers to meet their customers, and helps Amazon continuously innovate on behalf of all customers. Key job responsibilities As a Machine Learning Applied Scientist, you will: * Conduct deep data analysis to derive insights to the business, and identify gaps and new opportunities * Develop scalable and effective machine-learning models and optimization strategies to solve business problems * Run regular A/B experiments, gather data, and perform statistical analysis * Work closely with software engineers to deliver end-to-end solutions into production * Improve the scalability, efficiency and automation of large-scale data analytics, model training, deployment and serving * Conduct research on new machine-learning modeling to optimize all aspects of Sponsored Products and Brands business About the team We are pioneers in applying advanced machine learning and generative AI algorithms in Sponsored Products and Brands business. We empower every customer with a customized discovery experiences from back-end optimization (such as customized response prediction models) to front-end CX innovation (such as widgets), to help shoppers feel understood and shop efficiently on and off Amazon.
US, WA, Seattle
MULTIPLE POSITIONS AVAILABLE Employer: AMAZON WEB SERVICES, INC. Offered Position: Research Scientist II Job Location: Seattle, Washington Job Number: AMZ9698004 Position Responsibilities: Perform and support the main psychometric aspects of exam development and operations, including but not limited to automated test assembly, item and test analyses, optimal item bank design, job task analysis, standard setting, quality assurance, and project planning. Conduct main aspects of psychometric analysis in operational work including performing item analysis using psychometric methods, building optimal test forms and pools via optimization techniques, analyzing and monitoring item bank health, setting pass standards via standard setting studies, and supporting Job Task Analysis (JTA) to define and refresh test blueprints. Conduct main aspects of psychometric analysis in developing and applying statistical and psychometric modeling to evaluate and ensure AWS certification exams’ validity, reliability, applicability, efficiency, and accuracy. Participate in research projects to improve existing operational processes and quality using advanced techniques such as Machine Learning (ML), statistical modeling, Natural Language Processing (NLP), Generative Artificial Intelligence (GenAI), etc. Develop automation code using R or Python for psychometric workflow pipeline and other tasks to improve operational efficiencies. Present, interpret, and communicate the results of analyses to stakeholders through written and oral reports. Follow the accreditation standards set by ISO/IEC:2012 17024 and the National Council for Certifying Agencies (NCCA) as they relate to valid psychometric practices. Engage with the professional community through conferences and publications. Position Requirements: PhD or foreign equivalent degree in Statistics, Psychometrics, Educational Measurement, Quantitative Psychology, Data Science, Industrial-Organizational (I/O) Psychology, or a related field and one year of research or work experience in the job offered, or as a Research Scientist, Research Assistant, Software Engineer, or a related occupation. Must have 1 year of experience in the following skill(s): 1. large-scale education, licensure, or certification assessment programs. 2. operational psychometric tasks on large-scale education, licensure, or certification assessment programs including item analysis, equating and scaling, item response theory, classical test theory, form and pool assembly, item bank health analysis, standard setting, and job task analysis. 3. at least one of the complex test designs such as linear-on-the-fly testing (LOFT), computerized adaptive testing (CAT). 4. at least one of the following areas including machine learning (ML) or natural language processing (NLP). 5. Programming skills in at least one script-based programming language (R, Python). Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation. 40 hours / week, 8:00am-5:00pm, Salary Range $136,000/year to $184,000/ 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.#0000
US, NY, New York
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through novel 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 ecosystem. 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. Key job responsibilities As a Senior Applied Scientist on our team, you will * Develop AI solutions for Sponsored Brands advertiser and shopper experiences. Build recommendation systems that leverage generative models to develop and improve campaigns. * You invent and design new solutions for scientifically-complex problem areas and/or opportunities in new business initiatives. * You drive or heavily influence the design of scientifically-complex software solutions or systems, for which you personally write significant parts of the critical scientific novelty. You take ownership of these components, providing a system-wide view and design guidance. These systems or solutions can be brand new or evolve from existing ones. * Define a long-term science vision and roadmap for our Sponsored Brands advertising business, driven from our customers' needs, translating that direction into specific plans for applied scientists and engineering teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. * Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end; * Design and conduct A/B experiments to evaluate proposed solutions based on in-depth data analyses; * Think big about the arc of development of Gen AI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems * Effectively communicate technical and non-technical ideas with teammates and stakeholders; * Translate complex scientific challenges into clear and impactful solutions for business stakeholders. * Mentor and guide junior scientists, fostering a collaborative and high-performing team culture. * Stay up-to-date with advancements and the latest modeling techniques in the field About the team We are on a mission to make Amazon the best in class destination for shoppers to discover, engage, and purchase relevant products, from brands that are relevant to them. In this role, you will design and implement Gen AI solutions that help millions of advertisers create more effective ad campaigns with intelligent recommendations, while improving the overall experience at Amazon's global scale.
US, WA, Seattle
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading 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. Key job responsibilities We are looking for an Applied Science Manager to lead the Insights & Prompt Generation vertical within the Conversational Discovery Experiences (CAX) team in Sponsored Products and Brands (SPB). This team owns prompt generation, quality, personalization, and coverage for Sponsored Prompts, a new conversational ad format powered by large language models (LLMs) that helps shoppers discover products across Amazon.com. As an Applied Science Manager, you will lead a team of applied scientists and engineers to build and scale the prompt generation pipeline, develop new prompt themes and quality frameworks, and drive coverage expansion across all surfaces. You will own the science roadmap for prompt generation and personalization. You will define the metrics that measure prompt effectiveness and drive experimentation to improve CTR, helpfulness, and advertiser outcomes. This role requires strong technical depth in NLP, LLMs, and information retrieval, combined with the ability to manage and grow a science team, set research direction, and influence product strategy. You will work across organizational boundaries with engineering, product, and business teams to translate science investments into measurable business impact.