The research behind Alexa’s popular whispered speech

According to listener tests, whispers produced by a new machine learning model sound as natural as vocoded human whispers.

In 2018, Amazon launched a feature in the U.S. that enables Alexa to whisper back when whispered to, a feature that was expanded to all Alexa locales in November 2019. In a paper appearing in the January 2020 issue of the journal IEEE Signal Processing Letters, we describe the research that enabled that expansion.

A spectrogram of normally voiced speech and its conversion into a whispered-speech spectrogram
A spectrogram of normally voiced speech (left) and the result of applying our whispered-speech voice conversion model to it.
Stacy Reilly

Our goal: convert normal speech into whispered speech while maintaining high naturalness and speaker identity. In the paper, we examined three different techniques for performing this conversion: a handcrafted digital-signal-processing (DSP) technique based on acoustic analysis of whispered speech and two different machine learning techniques, one that uses Gaussian mixture models (GMMs) and another that uses deep neural networks (DNNs). We evaluated all three methods through listener studies using the MUSHRA (multiple stimuli with hidden reference and anchor) methodology.

We found that, when the machine learning models were applied to the same speaker they had been trained on, their performance was roughly equivalent, and both outperformed the handcrafted signal processor. But the DNN model generalized much more readily to multiple and unfamiliar speakers.

Digital signal processorDeep neural network
U.S. English
Indian English
Mexican Spanish
German
Japanese

Translations of the sentence "Setting the temperature to 70 degrees Fahrenheit" in four languages and five locales, converted into whispered speech by both a conventional digital signal processor and our new deep-learning model.

In 2017, we used the DSP technique to add whisper to all the voices available through Amazon Polly, the text-to-speech service provided to Amazon Web Services customers. It was based on a large body of scientific literature analyzing the acoustic differences between whispered and fully voiced speech.

The two machine learning techniques (GMMs and DNNs) are instances of an approach called voice conversion. Voice conversion represents the speech signal using a set of acoustic features and learns to map the features of normally voiced speech onto those of whispered speech.

GMMs attempt to identify a range of values for each output feature — a Gaussian distribution over outputs — that correspond to a related distribution of input values. The combination of multiple distributions is what makes it a “mixture”. DNNs are dense networks of simple processing nodes whose internal settings are adjusted through a training process in which the network attempts to predict the outputs associated with particular sample inputs.

Voice conversion techniques have been used for a long time to make recordings of a source speaker sound more like those of a target speaker. They've also been used to try to reconstruct normal speech from whispered speech — in the case of laryngectomy patients, for instance. But this is the first time that they have been applied to the reverse problem.

We used two different data sets to train our voice conversion systems, one that we produced ourselves using professional voice talent and one that is a standard benchmark in the field. Both data sets include pairs of utterances — one in full voice, one whispered — from many speakers.

Graph showing MUSHRA scores for voice conversion techniques and human speech
MUSHRA scores for the naturalness of recorded speech (Rec), vocoded recorded speech (Oracle), and our three experimental systems.

Like most neural text-to-speech systems, ours passes the acoustic-feature representation to a vocoder, which converts it into a continuous signal. To evaluate our voice conversion systems, we compared their outputs to both recordings of natural speech and recordings of natural speech fed through a vocoder (our “oracle”). This allowed us to gauge how well the voice conversion system itself was performing, independent of any limitations imposed by the need for vocoding.

figure2.png
Naturalness (a) and speaker similarity (b) scores for our neural network when trained on both our in-house data and an industry-standard public data set. The five country codes (AU, CA, GB, IN, and US) indicate the regions represented by the five speakers in our in-house data set; the four alphanumeric codes represent individual speakers (two male, two female) in the public data set. Rec is a raw recording, All the version of the model trained on all speakers, SD (speaker-dependent) the version trained on a single speaker, Excl the version trained on all but the test speaker, and DSP the digital signal processor.

In our first set of experiments, we trained the voice conversion systems on data from individual speakers and then tested them on data from the same speakers. We found that, while the raw recordings sounded most natural, whispers synthesized by our voice conversion models sounded more natural than vocoded human speech.

We then explored the ability of the conversion models to generalize to unseen speakers. First, we trained models on the full set of speakers from each data set and applied them to the same speakers. Then we trained the models on all but one speaker from each data set and applied it only to the held-out speaker.

In our experiments, we used only the open-source WORLD vocoder. However, in the version of our system that we have deployed to customers in all Alexa locales, we use a state-of-the-art neural vocoder that enhances the quality of the whispered speech even further. That’s the version that we used to generate the samples above.

About the Author
Marius Cotescu is an applied scientist in the Amazon Text-to-Speech group.

Work with us

See More Jobs
US, WA, Seattle
Global Talent Management (GTM) is centrally responsible for creating and evolving Amazon’s human capital and talent programs and processes.People Science Team within GTM is a growing start-up team with direct impact on Amazonians across all of our businesses and locations around the world. We play a crucial role in ensuring top notch data products and insights facilitate our growth and development of talent in intelligent and curious ways. We regularly use data to pitch ideas and drive conversations with Amazon’s Senior Vice President of HR and other executives about how to improve existing talent programs to solve organizational problems focused on (but not limited to) talent differentiation, talent movement, employee-role matching, product integration, promotion practices, organization design and succession planning, and diversity and inclusion, or invent new ones that address the evolving needs of our diverse employee base.We are looking for a seasoned Senior Data Scientist to help shape analytics and research roadmap and enable data-driven innovation that fuel our rapidly scaling talent management mission.You will partner closely with product and program owners, as well as scientists and engineers from other disciplines (e.g. economics, statistics, business intelligence, data engineering) with a clear path to business impact. You develop innovative and even frighteningly bold plans and ideas to discover new ways to advance our goals. You will be expected to be a thought leader as we chart new courses with our rapidly growing employee populations, and lead the way in experimenting new ideas that have not yet been explored.Successful candidates will have a deep knowledge of computing statistical and machine learning methods for large scale prediction problems -or- a deep knowledge of computational optimization methods and mathematical modelling, the ability to map models into production-worthy code, the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers, and the excitement to take iterative approaches to tackle big, long term problems.Key Responsibilities:· Participate in scoping and planning of GTM’s data science roadmap· Uncover drivers, impacts, and key influences on talent outcomes· Develop predictive and optimization models for key applications· Navigate a variety of data sources, such as enterprise data, customize surveys, focus groups, and/or external data sources· Ability to distill informal customer requirements into problem definitions, dealing with ambiguity and competing objectives· Work in expert cross-functional teams delivering on demanding projects· Functionally decompose complex problems into simple, straight-forward solutions
US, WA, Seattle
Do you want to join a fast-paced innovative team who use cutting edge analytical tools and techniques to help our new and existing customers? Are you excited by the prospect of analyzing and huge amounts of data and creating state of the art algorithms to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? Amazon Web Service (AWS) marketing team is looking for a Senior Applied to join our & Science team. The successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail, an ability to work in a fast-paced and ever-changing environment, and a desire to help share the overall business.Major responsibilities:· Use data analysis, statistical and techniques to develop solutions to improve customer experience, retention and drive strategic product(s) adoption· Lead development and implementation of new algorithms· Coach other on the team with a systematical peer review and & model proposal evaluation· Design, development and evaluation of highly innovative models to help the AWS marketing organization with business decision making and address quantitative problems· Analyze and understand large amounts of Amazon’s complex and discrete datasets about AWS customers in order to understand our customer behavior and help guide complex business decisions.· Establish scalable, efficient, automated processes for large scale data analyses, and model development, validation and implementation· Work closely with other marketing teams to drive model/solution development and their implementation· Work closely with team of BI engineers to improve data quality and operationalize new solutions· Communicate and influence senior management· and implement novel and statistical approaches
US, WA, Seattle
Amazon's Payment Products team manages Amazon branded payment offerings globally. These products are growing rapidly and we are continuously adding new market-leading features and launching new products. Our payments products (Amazon Co-Branded Credit Cards, Private Labeled Credit Cards, Non-Amazon Branded Credit Cards, Shop with Points and cross-currency converter) provide the most innovative payment experience on and off Amazon. Our team of high caliber software developers, statisticians, analysts and product managers use rigorous quantitative approaches to ensure that we target the right product to the right customer at the right moment, managing tradeoffs between click through rate, approval rates and lifetime value. We leverage the wealth of Amazon’s information to build a wide range of probabilistic models, set up experiments that ensure that we are thriving to reach global optimums and leverage Amazon’s technological infrastructure to display the right offerings in real time. We work closely with product managers to understand their business, collect requirements and deliver high value analytics and insights for the Payments team that drive acquisition, usage and loyalty. Our petabytes of data have the ability to improve the shopping experience for hundreds of millions of consumers worldwide. Our goal is to delight our customers with their purchasing experience. Those of us who love to work with data see this as the pinnacle of opportunities that you cannot find anywhere else in the world.We are seeking an exceptionally talented individual to improve our analytic capabilities. This is an opportunity to join a group with a broad charter and stakeholders across Amazon. In this role, you will be working in one of the world's largest and most complex data warehouse environments. You should be passionate about working with huge datasets and be someone who loves to bring data together to answer business questions. You should have deep expertise in creation and management of datasets and the proven ability to translate the data into meaningful insights. You will have to work with a group of applied and data scientists and play an integral role in strategic decision-making.The right candidate will possess excellent business and communication skills, work with business owners to develop and define key business questions, and prioritize the work across your team in order to support the broader business initiatives. You should have a solid understanding of efficient and scalable data mining and an ability to use the data in financial and statistical modeling.
DE, BW, Tuebingen
Are you interested in working on fundamental scientific challenges to create fair, explainable, and powerful AI? Would you like to contribute to the development of the future generation of cognitive services at Amazon Web Services?As a Research or Applied Scientist, you will be working on cutting edge research projects at the intersection of machine learning applications and theory. You will be part of an ambitious team of scientists and software engineers with the goal of solving hard scientific problems at scale that will lead to novel products that are impossible to do right now.Our teams are doing very interesting work in causality and adversarial robustness, ML in health, image processing, fairness, privacy, and accountability in addition to research on reinforcement learning'We are interested at fundamental problems in machine learning that are the building blocks of future products and services. We need to draw connections from statistics, deep learning, probabilistic reasoning, scientific programming, and rigorous math, to make advances to teach computers to understand the world around us. This includes advances in theoretical areas and design of novel algorithmic solutions. Due to the nature of the problems that we study, we build a highly technical team that combines a diverse skill set where everyone is eager to grow and learn.We offer the possibility to supervise PhD students and visiting interns as well as collaboration in an excellent academic environment that includes researchers on all levels in their career.
US, WA, Seattle
Are you excited about developing state-of-the-art Machine Learning, Natural Language Processing, Deep Learning and Computer Vision algorithms and designs using large data sets to solve real world problems? Do you have proven analytical capabilities and can multi-task and thrive in a fast-paced environment? Do you want to build a foundation for your career after your Master's or Ph.D program at an industry-leading company?You enjoy the prospect of solving real-world problems that, quite frankly, have not been solved at scale anywhere before. Along the way, you’ll get opportunities to be a fearless disruptor, prolific innovator, and a reputed problem solver—someone who truly enables machine learning to create significant impacts.As an Applied Scientist, you will bring statistical modeling and machine learning advancements to data analytics for customer-facing solutions in complex industrial settings. You will be working in a fast-paced, cross-disciplinary team of researchers who are leaders in the field. You will take on challenging problems, distill real requirements, and then deliver solutions that either leverage existing academic and industrial research, or utilize your own out-of-the-box pragmatic thinking. In addition to coming up with novel solutions and prototypes, you may even need to deliver these to production in customer facing productsWe offer flexible year round start dates for both intern and fulltime roles.Notable teams include:· Amazon AI (AWS)· Alexa ML· Alexa Brain· Amazon Go· Lab 126· Personalization· Ad Tech· AWS
CA, BC, Vancouver
The mission of the Economic Technology (ET) team is to disrupt decision processes at Amazon in order to generate outsized long-term value gains. We are an interdisciplinary team of Economists, Engineers, and Scientists incubating and building day one solutions using cutting-edge technology, to solve some of the toughest business problems at Amazon. We find opportunity wherever manual processes will not scale, where arbitrary heuristic rules struggle to keep up, or where key information is missing. We apply Big Data Analytics, Machine Learning, Causal Inference, and Econometric/Economic Methodologies to derive actionable insights about the complex economy of Amazon’s retail business.As a science and product manager on ET, you will:· Work on a variety of challenging problems that have the potential to significantly impact Amazon’s business and competitive position.· Learn and grow by being exposed to multiple organizational problems in a short time frame.· Discover, define, and apply scientific, engineering, and business best practice while delivering science for $1B+ opportunities.· Partner with scientists, economists, and engineers to help deliver scalable ML and econometric models while building tools to help our customers gain and apply insights.· Providing technical and scientific guidance to your team members.You will be responsible for rethinking the assumptions behind how traditional infrastructure and services are built and maintained in order to create the agility necessary to develop and incubate new solutions to challenging business problems. You will draw from a deep and broad technical expertise to own large and complex multi-business deliverables.This role is critical to ensuring the success of projects supporting millions of customers in their shopping missions as well as a significant portion of Amazon’s revenue. A successful candidate will bring deep technical and software expertise, and strong business judgment, to help us execute effectively on the complex roadmaps. In this role, you will need to manage cross-functional communication, identify & mitigate risks to efficient delivery, decompose ambiguous problems into workable plans, and to lead execution across multiple teams.
CA, BC, Vancouver
The Economic Technology team (ET) is looking for an Applied Scientist to join our team in building Reinforcement Learning solutions at scale. The ET applies Machine Learning, Reinforcement Learning, Causal Inference, and Econometrics/Economics to derive actionable insights about the complex economy of Amazon’s retail business. We also develop Statistical Models and Algorithms to drive strategic business decisions and improve operations. We are an interdisciplinary team of Economists, Engineers, and Scientists incubating and building day one solutions using cutting-edge technology, to solve some of the toughest business problems at Amazon.You will work with business leaders, scientists, and economists to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable distributed services. You will partner with scientists, economists, and engineers to help invent and implement scalable ML, RL, and econometric models while building tools to help our customers gain and apply insights.This is a unique, high visibility opportunity for someone who wants to have business impact, dive deep into large-scale economic problems, enable measurable actions on the Consumer economy, and work closely with scientists and economists. We are particularly interested in candidates with experience building predictive models and working with distributed systems.As an Applied Scientist, you bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions.
CA, ON, Toronto
Amazon is looking for a passionate, talented, and inventive Scientist with a strong machine learning background to help build industry-leading Speech and Language technology. Our mission is to push the envelope in Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), and Audio Signal Processing, in order to provide the best-possible experience for our customers.As a Scientist, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art in spoken language understanding. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in spoken language understanding.We are hiring in all areas of spoken language understanding: ASR, NLU, text-to-speech (TTS), and Dialog Management.Position Responsibilities: · Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications. · Develop and/or apply statistical modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. · Routinely build and deploy ML models on available data. · Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists.
US, CA, San Francisco
Alexa.com is seeking a creative, entrepreneurial, and customer-obsessed Applied Scientist who can apply cutting edge research and state-of-the-art machine learning algorithms to the development of scalable AI marketing analytics solutions. The ideal candidate has a broad and deep background in machine learning, is passionate about science, is highly driven to learn and deploy new technologies, thrives in a fast-paced environment that requires the development of solutions to ambiguous and challenging problems, and enjoys collaborating with both technical and nontechnical peers.At Alexa.com, we solve ML problems in natural language processing and understanding, search relevance and ranking, and digital behavior measurement and prediction. As part of our AI team, you will work as a hands-on practitioner and technical leader in multiple areas such as statistical modeling, NLP and NLU, dimensionality reduction, and deep learning. You will formulate and test hypotheses, evaluate and implement ML techniques, and deliver new production services that will be used by millions of users worldwide.We have been gathering and analyzing data from online sources for more than 20 years, with terabytes of archived crawl data, a data-contributing panel of millions of users in countries around the world, and millions of unique website visitors each month. This position provides the qualified candidate with an opportunity to join our smart, motivated team and to directly impact our business.Alexa.com is a subsidiary of Amazon.com serving millions of users worldwide and building the next generation of marketing analytics services. Our mission is to be most invaluable and trusted source of ground-breaking insights into digital behavior that customers use to win their audience and accelerate growth. For more information, visit www.alexa.com.Core Responsibilities· Develop novel modeling techniques for pattern recognition, prediction, classification, and other complex data science problems· Develop prototypes and collaborate with stakeholders to assess the feasibility of selected approaches· Write high quality code and contribute to our codebase of scientific applications using relevant technologies· Build well-iterated models or analyses which reduce noise and maximize performance and accuracy· Contribute to strategic planning and project management for a variety of technical initiatives· Effectively communicate with customers, senior management, and colleagues with diverse roles and technical backgrounds· Document methodologies and increase our institutional knowledge based on experimental results and operationalized solutions
US, WA, Seattle
Are you passionate about conducting research to drive real behavioral change and inform front line managers and leaders in making more effective decisions? Would you love to see your research in practice, impacting Amazonians globally and improving the employee experience? If so, you should consider joining our Research team on Amazon Connections.Amazon Connections is an innovative program that gives Amazonians a confidential and effective way to give feedback on the workplace to help shape the future of the company and improve the employee experience. By asking employees quick questions every day, Connections leverages real time information to learn more about their experiences and introduce positive changes with internal business partners around the world. We maximize the value of the employee voice.We are seeking Assessment and measurement Scientists with expertise developing assessment and survey content that is relevant to the respondent, minimizes contextual and cognitive biases, and captures responses true to what was intended with the item design. This person will possess some knowledge of different item and response options methods and a psychometrics background, scientific survey methodology, and computing various content integrity and validity analyses.In this role, you will support the content development and execution strategy. Content will elicit employee responses that will help managers and leaders inspect, but also understand key drivers and moderators for key research streams. These include (but are not limited to) attrition, engagement, productivity, diversity, and culture. You will also support developing research-based recommendations that will be auto generated to improve ‘just in time’ manager feedback and leader decision making at scale.You will conduct content research to reduce or address measurement error and generate metrics to evaluate content quality. You will work with a team of psychologists, economists, ML scientists, UX researchers, dev engineers, and product managers to inform and build product features to surface deeper people and business insights for our leaders.What you'll do:· Execute a scalable global content development and research strategy Amazon-wide· Conduct psychometrics analyses to evaluate integrity and practical application of content· Develop and iterate on testing, experimenting, and evaluating content prior to global launch· Combine quantitative and qualitative data to inform research· Develop and innovate on new measurement approaches· Identify research streams to evaluate how to mitigate or remove sources of measurement error· Partner closely and drive effective collaborations across multi-disciplinary research and product teams· Manage full life cycle of large scale research programs (Develop strategy, gather requirements, manage and execute)
US, WA, Seattle
MULTIPLE POSITIONS AVAILABLEEntity: Amazon Web Services, Inc.Position: Data Scientist IIILocation: Seattle, WAPosition ResponsibilitiesUse data analysis, statistical and machine learning techniques to develop solutions to improve customer experience and retention, and drive strategic product adoption. Design, develop and evaluate highly innovative models to help the AWS marketing organization make business decisions and address quantitative problems. Analyze and understand large amounts of Amazon’s complex and discrete datasets about AWS customers inorder to understand our customer behavior and help guide complex business decisions. Establish scalable, efficient, automated processes for large scale data analyses, model development, validation and implementation. Work closely with other marketing teams to drive model/solution development and implementation. Work closely with a team of Business Intelligence engineers to improve data quality and operationalize new solutions. Communicate with and influence senior management. Research and implement novel machine learning and statistical approaches.Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation #0000
US, NY, New York
Amazon.com is looking for a motivated individual with strong analytical skills to join our AWS Automated Reasoning Group.Need more details for JD- Interact with various groups to develop an understanding of their security and safety requirements.- Apply the acquired knowledge to build tools find problems, or show the absence of security/safety problems.- Implement these tools through the use of SAT, SMT, BDDs, and various concepts from programming languages, theorem proving, formal verification and constraint solving.- Perform analysis of the customer systems using tools developed in-house or externally provided- Find exploits and fixes for security vulnerabilities, and software to automate this process.- Create software prototypes to verify and validate the devised solutions methodologies; integrate the prototypes into production systems using standard software development tools and methodologies.
US, WA, Seattle
Amazon is looking for a passionate, talented, and inventive Scientist with a strong machine learning background to help build industry-leading Speech and Language technology. Our mission is to push the envelope in Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), and Audio Signal Processing, in order to provide the best-possible experience for our customers.As a Scientist, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art in spoken language understanding. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in spoken language understanding.We are hiring in all areas of spoken language understanding: ASR, NLU, text-to-speech (TTS), and Dialog Management.
US, WA, Seattle
The Alexa Science and Machine Learning team’s goal is to make voice interfaces ubiquitous and as natural as speaking to a human. Deep learning at this massive scale requires new research and development. The team is responsible for cutting-edge research and development in virtually all fields of Human Language Technology: Automatic Speech Recognition (ASR), Artificial Intelligence (AI), Natural Language Understanding (NLU), Question Answering, Dialog Management, and Text-to-Speech (TTS).As part of our speech and language team, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in spoken language understanding. Your work will directly impact millions of our customers in the form of products and services that make use of speech and language technology. You will gain hands on experience with Amazon’s heterogeneous speech, text, and structured data sources, and large-scale computing resources to accelerate advances in spoken language understanding. It is not imperative to have experience in ASR. We have scientists building production models released to Echo customers, who had no prior speech experience, but very strong in ML, statistics, coding (and “can do” spirit!).We are hiring in all areas of spoken language understanding: ASR, NLU, text-to-speech (TTS), and Dialog Management.
US, WA, Seattle
Amazon.com strives to be Earth's most customer-centric company where people can find and discover anything they want to buy online. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment.Economists at Amazon will be expected to work directly with senior management on key business problems faced in retail, international retail, cloud computing, third party merchants, search, Kindle, streaming video, and operations. Amazon economists will apply the frontier of economic thinking to market design, pricing, forecasting, program evaluation, online advertising and other areas. You will build econometric models, using our world class data systems, and apply economic theory to solve business problems in a fast moving environment. Economists at Amazon will be expected to develop new techniques to process large data sets, address quantitative problems, and contribute to design of automated systems around the company.
US, WA, Seattle
How can we help Amazonians make more informed decisions about talent? How can we ensure our talent strategy and guidance is optimized for long-term value? How can we architect insights and systems to anticipate business talent demand and proactively identify and develop talent to fill these future needs? How do we effectively leverage econometrics, predictive algorithms, machine learning, UX design, and world-class product development to answer these critical questions? These are among the most important challenges at Amazon today.We are looking for a world-class scientist who wants to help us define the future of talent evaluation, development, and management at Amazon. You will leverage data, customer feedback, algorithm design, machine learning, econometrics, and predictive analytics to help define new ways to evaluate, visualize, predict, and understand talent outcomes and decisions like hiring, promotions, and transfers. After you have developed peer-reviewed scientific solutions to these unique problems, you will partner with economists, data scientists, software engineers, data engineers, applied scientists, product managers, and UX designers to deliver your solution to tens of thousands of internal customers through world-class product experiences. This is an opportunity to fundamentally redefine talent management for one of the largest and most complex workforces in the world.If you have an entrepreneurial spirit, are passionate about helping those around you reach their fullest human potential, know how to deliver, and view technology as a way to disrupt and reimagine talent management processes, we want to talk to you.Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation
US, WA, Seattle
Amazon is the second largest private employer in the country, and encounters the expected challenges from managing such a large and diverse workforce. We are looking for a senior economist to research topics touching upon all aspects of HR, including: workforce planning, recruiting, employee engagement, retention, development, and compensation.The ideal candidate will be able to: (1) use economic theories to structure ambiguous problems; (2) define proper metrics and assemble unique datasets to test hypotheses; (3) assess and interpret (causal) empirical relationships using data; and (4) design and test how incentives affect behavior, taking into account dynamic long-term and strategic factors. The candidate should have strong communication skills, and be able to use their analysis to articulate a true and coherent story on the impact Amazon has had on workers, the market, and the economy. The individual is expected to work closely with business leaders, and communicate clearly through various means, including research papers and public speaking.
US, WA, Bellevue
Are you interested in the field of data science? Do you enjoy diving deep into hard technical problems and coming up with solutions that enable successful products that improve the lives of people in a meaningful way?Amazon teams are using their domain expertise to invent, design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. We are looking for motivated Data Scientists with excellent leadership skills, and the ability to develop, automate, and run analytical models of our systems. If you have a demonstrated ability to manage medium-scale modeling projects, identify requirements, build methodology and tools that are statistically grounded, and experience collaborating across organizational boundaries, then come build the future with us.Key Job Responsibilities:As a Data Scientist, you will own your work from concept through to execution. This role will give you the opportunity to build tools and support structures needed to analyze data, dive deep into data to resolve root cause of systems errors and changes, and present findings to business partners to drive improvements.
US, WA, Seattle
Join us in a historic endeavor to make Computer Vision accessible to the world with breakthrough research!The AWS Computer Vision science team has a world-leading team of researchers and academics, and we are looking for world-class colleagues to join us and make the AI revolution happen. Our team of scientists have developed the algorithms and models that power AWS computer vision services such as Amazon Rekognition and Amazon Textract. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and workshops.AWS is the world-leading provider of cloud services, has fostered the creation and growth of countless new businesses, and is a positive force for good. Our customers bring problems which will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world.Our research themes include, but are not limited to: few-shot learning, transfer learning, unsupervised and semi-supervised methods, active learning and semi-automated data annotation, large scale image and video detection and recognition, face detection and recognition, OCR and scene text recognition, document understanding, and 3D scene and layout understanding.We are located in Seattle, Pasadena, Palo Alto, Atlanta (USA) and in Haifa and Tel Aviv (Israel).
US, WA, Seattle
Customer Service Worldwide Defect Elimination (WWDE) is responsible for driving the elimination of customer experience defects across Amazon. One of the mechanisms we use to eliminate defects is the Andon Cord. In the last year WWDE has heavily invested in rebuilding the foundation of this mechanism and is now looking to expand the defect elimination impact of it by leveraging Machine Learning to detect customer experience defects. To this we are looking for a highly motivated, customer obsessed, and results driven Sr. Data Scientist. As a Sr. Data Scientist, you will help drive Amazon towards a defect free customer experience by detecting anomalies, identifying their root cause and enabling business teams to resolve the issues.In this role, you will apply modeling and machine learning techniques to develop scalable solutions and deliver insights that improve the customer experience across a worldwide market. You will partner with engineers, product managers, and other analytical leaders to drive business impact. Our environment is fast-paced and requires someone enthusiastic, flexible, detail-oriented, analytical, and comfortable working with multiple teams and managing competing priorities. This role has significant impact on the customer experience by directing customers’ feedback to Amazon’s leaders, who will drive action and ensure that negative experiences are eliminated.Key Responsibilities· Develop ways to identify and deep-dive anomalous customer experiences, explain why they happen and identify potential solutions.· Attribute features to identified anomalies in order to classify the root cause for business teams to action.· Develop detection models using high-level modeling languages such as R and in software languages such as Python or Scala.· Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters.· Translate business questions and concerns into quantitative questions that can be answered with data using sound methodologies.· Create, enhance, and maintain technical documentation, and present to other scientists, engineers and business leaders.· Drive best practices on the team; mentor and guide junior members to achieve their career growth potential.