"This technology will be transformative in ways we can barely comprehend"

A judge and some of the finalists from the Alexa Prize Grand Challenge 3 talk about the competition, the role of COVID-19, and the future of socialbots.

Human beings are social creatures, and conversations are what connect us—they enable us to share everything from the prosaic to the profound with the people that matter to us. Living through an era marked by pandemic-induced isolation means many of those conversations have shifted online, but the connection they provide remains essential.

So what happens when you replace one of the human participants in a conversation with a socialbot? What does it mean to have an engaging conversation with an AI assistant? How can that kind of conversation prove to be valuable, and can it provide its own kind of connection?

Application period for next Alexa Prize challenge opens

The Amazon Alexa Prize team encourages all interested teams to apply for the Grand Challenge 4 by 11:59 p.m. PST on October 6, 2020.

The participants in this year’s Alexa Prize contest are driven by those questions. Amazon recently announced that a team from Emory University has won the 2020 Alexa Prize. We talked to that team, along with a judge from this year’s competition, as well as representatives from the other finalist teams at Czech Technical University, Stanford University, University of California, Davis, and University of California, Santa Cruz. We wanted to learn what drives them to participate, how COVID-19 has influenced their work and what they see as the possibilities and challenges for socialbots moving forward.

Alexa Prize Grand Challenge 3 winners share their work | Amazon Science

Q: What inspired you to participate in this year’s competition?

Sarah Fillwock, team leader, Emora, Emory University: We had a group of students who were interested in dialogue system research, some of whom had actually participated in the Alexa Prize in its previous years, and we all knew that the Alexa Prize offers a really unique opportunity for anyone interested in this type of work. It is really exciting to use the Alexa device platform to launch a socialbot, because we are able to get hundreds of conversations a day between our socialbot and human users, which really allows for quick turnaround time when assessing whether or not our hypotheses and strategies are improving the performance of our dialogue system.

Marilyn Walker, faculty advisor, Athena, University of California, Santa Cruz: In our Natural Language and Dialogue Systems lab, our main research focus is dialogue management and language generation. Conversational AI is a very challenging problem, and we felt like we could have a research impact in this area. The field has been developing extremely quickly recently, and the Alexa Prize offers an opportunity to try out cutting-edge technologies in dialogue management and language generation on a large Alexa user population.

Amazon Alexa Prize Finalists 2020
The five Alexa Prize finalist teams: Czech Technical University in Prague; Emory University; Stanford University; the University of California, Davis; and the University of California, Santa Cruz.

Vrindavan (Davan) Harrison, team leader, Athena, UCSC: As academics, our primary focus is on research. This year’s competition aimed at being more research-oriented, allowing the teams to spend more time on developing new ideas.

Kai-Hui Liang, team lead, Gunrock, University of California, Davis: Our experience in last year’s competition motivated us to join again as we realized there is still a large room for improvement. I’m especially interested in how to find topics that engage users the most, including trying different ways to elicit and reason about users’ interests. How can we retrieve content that is relevant and interesting, and make the dialog flow more naturally?

Jan Pichl, team leader, Alquist, Czech Technical University: Since the first year of the Alexa Prize competition, we have been developing Alquist to deliver a wide range of topics with a closer focus on the most popular ones. The first Alquist guided a user through the conversation quite strictly. We learned quickly that we needed to introduce more flexibility and let the user be "in charge". With that in mind, we have been pushing Alquist in that direction. Moreover, we want Alquist to manage dialogue utilizing the knowledge graph, and suggest relevant information based on the previously discussed topics and entities.

Christopher D. Manning, faculty advisor, Chirpy Cardinal, Stanford University: It was our first time doing the Alexa Prize, and the team really hadn’t done advance preparation, so it’s all been a wild ride—by which I mean a lot of work and stress for everyone on the team. But it was super exciting that we were largely able to catch up with other leading teams who have been doing the competition for several years.

Hugh Howey, judge and science fiction author: Artificial intelligence is a passionate interest of mine. As a science fiction author, I have the freedom to write about most anything, but the one topic I keep coming back to is the impact that thinking machines already have on our lives and how that impact will only expand in the future. So any chance to be involved with those doing work and research in the field is a no-brainer for me. I leapt at the chance like a Boston Dynamics dog.

Q: What excites you about the potential of socialbots?

Hugh Howey (Judge): This technology will be transformative in ways we can barely comprehend. Right now, the human/computer interface is a bottleneck. It takes a long time for us to tell our computers what we want them to do, and they'll generally only do that thing the one time and forget what it learned. In the future, more and more of the trivial will be automated. This will free up human capital to tackle larger problems. It will also bring us together by removing language barriers, by helping those with disabilities, and eventually this technology will be available to anyone who needs it.

Jinho D. Choi, faculty advisor, Emory: It has been reported that more than 44 million adults in US have mental health issues such as anxiety or depression. We believe that developing an innovative socialbot that comforts people can really help those with mental health conditions, who are generally afraid of talking to other human beings. You may wonder how artificial intelligence can convey a human emotion such as caring. However, humans have used their own creations, such as arts and music, to comfort themselves. It is our vision to advance AI, the greatest invention of humankind, to help individuals learn more about their inner selves so they can feel more positive about themselves, and have a bigger impact in the world.

Ashwin Paranjape, co-team leader, Stanford: As socialbots become more sophisticated and prevalent, increasing numbers of people are chatting with them regularly. As the name suggests, socialbots have the potential to fulfill social needs, such as chit-chatting about everyday life, or providing support to a person struggling with mental health difficulties. Furthermore, socialbots could become a primary user interface through which we engage with the world—for example, chatting about the news, or discussing a book.

Sarah Fillwock, Emory: Our experience in this competition has really solidified this idea of the potential of socialbots being value to people who need support and are in troubling situations. I think that the most compelling role for socialbots in global challenges is to provide a supportive environment to allow people to express themselves, and explore their feelings with regard to whatever dramatic event is going on. This is especially important for vulnerable populations, such as those who do not have a strong social circle or have reduced social contact with others, prohibiting them from being able to achieve the feeling of being valued and understood.

Q: What are the main challenges to realizing that potential?

Abigail See, co-team leader, Stanford: Currently, socialbots struggle to make sense of long, involved conversations, and this limits their ability to talk about any topic in depth. To do this better, socialbots will need to understand what a particular user wants—not only in terms of discussion topics, but also what kind of conversation they want to have. Another important challenge is to allow users to take more initiative, and drive the conversation themselves. Currently, socialbots tend to take more initiative, to ensure the conversation stays within their capabilities. If we can make our socialbots more flexible, they will be much more useful and engaging to people.

Sarah Fillwock, Emory: One major challenge facing the field of dialogue system research is establishing a best practice for evaluation of the performance of dialogue approaches. There is currently a diverse set of evaluation strategies that the research community uses to determine how well their new dialogue approach performs. Another challenge is that dialogues are more than just a pattern-matching problem. Having a back-and-forth dialogue on any topic with another agent tends to involve planning towards achieving specific goals during the conversation as new information about your speaking partner is revealed. Dialogues also rely a lot on having a foundation of general world knowledge that you use to fully understand the implications of what the other person is saying.

Amazon releases Topical Chat dataset

The text-based collection of more than 235,000 utterances will help support high-quality, repeatable research in the field of dialogue systems.

Marilyn Walker, UCSC: There’s a shortage of large annotated conversational corpora for the task of open-domain conversation. For example, progress in NLU has been supported by large annotated corpora, such as Penn Treebank, however, there are currently no such publicly available corpora for open-domain conversation. Also, a rich model of individual users would enable much more natural conversations, but privacy issues currently make it difficult to build such models.

Hugh Howey (Judge): The challenge will be for our ethics and morality to keep up with our gizmos. We will be far more powerful in the future. I only hope we'll be more responsible as well.

Q: What role has the COVID-19 pandemic played in your work?

Jurik Juraska, team member, UCSC: The most immediate effect the onset of the pandemic had on our socialbot was, of course, that it could not just ignore this new dynamic situation. Our socialbot had to acknowledge this new development, as that was what most people were talking about at that point. We would thus have Athena bring up the topic at the beginning of the conversation, sympathizing with the users' current situation, but avoiding wallowing in the negative aspects of it. In the feedback that some users left, there were a number of expressions of gratitude for the ability to have a fun interaction with a socialbot at a time when direct social interaction with friends and family was greatly restricted.

Kai-Hui Liang, UC Davis: We noticed an evident difference in the way Alexa users reacted to popular topics. For example, before COVID-19, many users gave engaging responses when discussing their favorite sports to watch, their travel experiences, or events they plan to do over the weekend. After the breakout of COVID-19, more users replied saying there’s no sports game to watch or they are not able to travel. Therefore, we adapted our topics to better fit the situation. We added discussion about their life experience during the quarantine (eg. how their diet has changed or if they walk outside daily to stay healthy). We also observed more users having negative feelings potentially due to the quarantine. For instance, some users said they feel lonely and they miss their friends or family. Therefore, we enhanced our comforting module that expresses empathy through active listening.

Abigail See, Stanford: As the pandemic unfolded, we saw in real time how users changed their expectations of our socialbot. Not only did they want our bot to deliver up-to-date information, they also wanted it to show emotional understanding for the situation they were in.

Sarah Fillwock, Emory: When COVID became a significant societal issue, we tried two things: we had an experience-oriented COVID topic where our bot discussed with people how they felt about COVID in a sympathetic and reassuring atmosphere, and we had a fact-oriented COVID topic that gave objective information. What we observed was that people had a much stronger positive reaction to the experience-oriented COVID-19 approach than the fact-oriented COVID-19 approach, and seemed to prefer it when talking. This really gave us some empirical evidence that social agents have a strong potential to be helpful in times of turmoil by giving people a safe and caring space to talk about these major events in their life since people responded positively to our approach at doing this.

Q: Lastly, are there any particular advancements in the fields of NLU, dialogue management, conversational AI, etc., that you find promising?

Jan Pichl, Czech Technical University: It is exciting to see the capabilities of the Transformer-based models these days. They are able to generate large articles or even whole stories that are coherent. However, they demand a lot of computation power during the training phase and even during the runtime. Additionally, it is still challenging to use them in a socialbot when you need to work with constantly changing information about the world.

Abigail See, Stanford: As NLP researchers, we are amazed by the incredible pace of progress in the field. Since the last Alexa Prize in 2018, there have been game-changing advancements, particularly in the use of large pretrained language models to understand and generate language. The Alexa Prize offers a unique opportunity for us to apply these techniques, which so far have mostly been tested only on neat, well-defined tasks, and put them in front of real people, with all the messiness that entails! In particular, we were excited to explore the possibility of using neural generative models to chat with people. As recently as the 2018 Alexa Prize, these models generally performed poorly, and so were not used by any of the finalist teams. However, this year, these systems became an important backbone of our system.

Sarah Fillwock, Emory: The work people have been putting into incorporating common sense knowledge and common sense reasoning into dialogue systems is one of the most interesting directions of the current conversational AI field. A lot of the common sense knowledge we use is not explicitly detailed in any type of data set as people have learned them through physical experience or inference over time, so there isn’t necessarily any convenient way to currently accomplish this goal. There have been a lot of attempts to see how far a language modeling approach to dialogue agents can go, but even using huge dialogue data sets and highly complex models still results in hit-and-miss success at common sense information. I am really looking forward to the dialogue approaches and dialogue resources that more explicitly try to model this type of common sense knowledge.


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Are you interested in applying your strong quantitative analysis and big data skills to world-changing problems? Are you interested in driving the development of methods, models and systems for strategy planning, transportation and fulfillment network? Are you interested to cooperate with Amazonians around the world? If so, then this is the job for you.Our team is responsible for creating core analytics tech capabilities, platforms development and data engineering. We develop scalable analytics applications and research modeling to optimize operation processes. We standardize and optimize data sources and visualization efforts across geographies, builds up and maintains the online BI services and data mart. You will work with professional data engineers, scientists, business intelligence engineers and product managers using rigorous quantitative approaches to ensure high quality data tech products for our customers around the world, including India, Australia, Brazil, Mexico, Singapore and Middle East.Amazon is growing rapidly and because we are driven by faster delivery to customers, a more efficient supply chain network, and lower cost of operations, our main focus is in the development of strategic models and automation tools fed by our massive amounts of available data. You will be responsible for building these models/tools that improve the economics of Amazon’s worldwide fulfillment networks in emerging countries as Amazon increases the speed and decreases the cost to deliver products to customers. You will identify and evaluate opportunities to reduce variable costs by improving fulfillment center processes, transportation operations and scheduling, and the execution to operational plans. You will also improve the efficiency of capital investment by helping the fulfillment centers to improve storage utilization and the effective use of automation. Finally, you will help create the metrics to quantify improvements to the fulfillment costs (e.g., transportation and labor costs) resulting from the application of these optimization models and tools.Major responsibilities include:· Translating business questions and concerns into specific analytical questions that can be answered with available data using Statistical and Machine Learning methods.· Design and develop complex mathematical, simulation and optimization models and apply them to define strategic and tactical needs and drive the appropriate business and technical solutions in the areas of inventory management, network flow, supply chain optimization, demand planning.· Apply theories of mathematical optimization, including linear programming, combinatorial optimization, integer programming, dynamic programming, network flows and algorithms to design optimal or near optimal solution methodologies to be used by in-house decision support tools and software.· Prototype models by using modeling and programming languages with efficient data querying and modeling infrastructure.· Communicate proposals and results in a clear manner backed by data and coupled with actionable conclusions to drive business decisions.· Collaborate with colleagues from multidisciplinary science, engineering and business backgrounds.· Manage your own process. Prioritize and execute on high impact projects, triage external requests, and ensure to deliver projects in time.
US, NY, Virtual Location - New York
Amazon delights millions of customers around the world. Meet the behind the scenes team that enables our Human Resource and Operations Leaders to make informed decisions. The Amazon PeopleInsight team builds reporting and analytics tools for our teams that fulfill customer promise every day. Whether it is Fulfillment Center team that delivers your Prime order in two days, our Amazon Locker team that lets you pick up your package anytime that is convenient for you, our Prime Now team getting you lunch in under an hour, or one of many more, the PeopleInsight group is there providing people metrics along the employee lifecycle for our global operations businesses. The PeopleInsight team is a collaborative group of Business Analysts, Business Intelligence Engineers, Data Engineers, Data Scientists, Product Managers, and Program Managers dedicated to empowering leaders and enabling action through data and science. We deliver workforce, associate experience, and leadership insights so Amazon leaders can focus their efforts in ways that will engage, retain and grow their associates.We are now recruiting for an exceptional Data Scientist, Worldwide OperationsThe ideal candidate will be:· A Well-Rounded Athlete –Like a true athlete, you understand that we succeed or fail as a team. You are always ready to step up beyond your core responsibilities and go the extra mile for the project and your team. You nimbly overcome barriers to deliver the best products more quickly than expected.· A Perpetual Student – You seek knowledge and insight. You challenge yourself to turn moments into master’s classes. Whether closing a gap, developing a new skill, or staying ahead of your industry, you revel in the joy of learning and growing.· A Skilled Communicator – You excel when interacting with business and technical partners whether you are chatting, sending a written message, or conducting a presentation.· A Trusted Advisor – You work closely with stakeholders to define key business needs and deliver on commitments. You enable effective decision making by retrieving and aggregating data from multiple sources and compiling it into a digestible and actionable format.· An Inventor at Heart – You innovate on behalf of your customer by proactively implementing improvements, enhancements, and customizations. Your customers marvel at your creative solutions to challenges they had not yet identified.· A Fearless Explorer – You are drawn to take on the hardest problems, navigate ambiguity, and battle skepticism. You never settle, even in the face of overwhelming obstacles.Roles and ResponsibilitiesSuccess in this role will include influencing within your team and mentoring peers. The problems you will consider will be difficult to solve and often require a range of data science methodologies combined with subject matter expertise. You will need to be capable of gathering and using complex data set across domains. You will deliver artifacts on medium size projects, define the methodology, and own the analysis. Your findings will affect important business decisions. Solutions are testable and reproducible. You will create documents and share findings in line with scientific best practices for both technical and nontechnical audiences.Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.
US, WA, Seattle
The Global Advertising Partner Development (GAPD) Economics team is looking for a driven Data Scientist who will take an active role in developing high-impact economic and data science analytics.The GAPD team helps suppliers, agencies, marketers, authors, content creators, designers, non-endemic advertisers and developers to scale their use of Amazon Advertising and grow their business by surfacing a diverse selection of products to millions of worldwide Amazon customers. We do this via software tools and marketing/engagement programs that enable developers and partners to better serve advertiser needs.Our team of scientists works closely with business stakeholders and uses econometrics, data science, and machine learning to uncover hidden opportunities for Marketing and Product Development. We are seeking a data scientist that quickly can approach large ambiguous problems and apply their technical and statistical knowledge to identify opportunities and insights that drive larger initiatives.As a Data Scientist, you will play an instrumental role in developing a new analytical agenda. Key responsibilities include:· Partnering with economists and senior team members to drive science and implement technical solutions using machine learning and econometrics· Collaborate with Data Engineers to help build data systems and metrics that continually improve data quality· Develop science-driven algorithms that yield robust recommendations along an advertiser’s lifecycle· Contribute to building a scalable experimental framework that help stakeholders make data-driven informed decisions· Communicate verbally and in writing to senior leaders with various levels of technical knowledge, educating them about your approach, as well as sharing insights and recommendations
US, WA, Seattle
The Amazon Air Science and Technology team is seeking a Senior Applied Scientist to be part of a team solving complex aviation operations problems to reduce cost and improve performance. This is a blue-sky role that gives you a chance to bring optimization modeling, statistical modeling, machine learning advancements to data analytics for customer-facing solutions in complex industrial settings.You will work closely with product, research science and technical leaders throughout Amazon Air, Amazon Delivery Technology and Supply Chain Optimization and will be responsible for influencing funding decisions in areas of investment that you identify as critical future product offerings. You will partner with software developers and data scientists to build end-to-end data pipelines and production code, and you will have exposure to senior leadership as we communicate results and provide scientific guidance to the business. You will analyze large amounts of business data, build the machine learning or optimization models that will enable us to continually delight our customers worldwide.The ideal candidate will have extensive experience in Science work, business analytics and have the aptitude to incorporate new approaches and methodologies while dealing with ambiguities. Excellent business and communication skills are a must to develop and define key business questions and build models that answer those questions. You should have a demonstrated ability to think strategically and analytically about business, product, and technical challenges. Further, you must have the ability to build and communicate compelling value propositions, and work across the organization to achieve consensus. This role requires a strong passion for customers, a high level of comfort navigating ambiguity, and a keen sense of ownership and drive to deliver results.Tasks/ Responsibilities:· Partnership with the engineering and operations to drive modeling and design for complex business problems.· Design and prototype decision support tools (product) to automate standardized processes and optimize trade-offs across the full decision space.· Contribute to the mid- and long-term strategic planning studies and analysis.· Lead complex transportation modeling analyses to aid management in making key business decisions and set new policies.
IE, Ireland
At Amazon we strive to be earth’s most customer centric company and data is a foundational component to making this happen. Are you curious about new platforms and technologies and have a desire to deliver world-class customer service? Are you excited by the idea of owning a problem and innovating on behalf of customers? Can you deal with ambiguity and keep up with the pace of a company whose cycles are measured in weeks, not years?The Device, Digital & Alexa Support (D2AS) team works with some of the fastest growth areas in the company. Amazon introduced the first Kindle in 2007 - since then, we have expanded to become the best-selling e-reader family in the world. We have gone beyond Kindle with our powerhouse Fire tablets, built for work and play with our Fire operating system. For streaming media lovers, we have created Amazon Fire TV, Fire TV Stick, and Fire TV Edition with voice search. Fire TV devices come with access to 500,000 movies, TV shows, and tens of thousands of channels, and apps. In 2014, we introduced Amazon Echo and Alexa, the voice service that powers Echo and other devices so customers can play music, control their smart homes, and get information, news, weather, and more using just their voice. Alexa is now integrated with over 20,000 third party devices from 3,500 brands. Alexa has 50,000 skills and developers in 180 countries.The Device, Digital & Alexa Support (D2AS) – Tech team is looking for a Manager, Data Science. This position will lead innovative science solutions and products to increase Amazon’s ability to personalize Customer Service: from models to understand customer needs, optimization models to identify the best solution, and personalized recommender systems. You will identify specific and actionable opportunities to solve existing Customer problems and develop science based products.The ideal candidate will have outstanding communication skills, strong technical knowledge, proven ability to lead a team scientists, with an innate drive to deliver results. She/he will be comfortable with ambiguity and will enjoy working in a fast-paced environment.Responsibilities:· Lead a team across technical job families - scientists and engineers· Manage a science agenda that balances short term deliverables with measurable business impact with long term projects.· Develop a roadmap/products for ML model deployment· Provide technical and scientific guidance to team members· Hire and develop top talent· Collaborate with business and software teams both within and outside of D2AS
US, WA, Seattle
Amazon is focused on protecting the health and safety of our employees while continuing to serve people who need our services more than ever. Regular testing on a global scale across all industries would both help keep people safe and help get the economy back up and running. But, for this to work, we as a society would need vastly more testing capacity than is currently available. Unfortunately, today we live in a world of scarcity where COVID-19 testing is heavily rationed. Until we have an effective vaccine available in billions of doses, high-volume testing capacity would be of great help, but getting that done will take collective action by NGOs, companies, and governments.The Role:We are a team of doers working passionately to apply cutting-edge advances in technology to solve real-world problems. As a Lead Scientist, you will work with a unique and gifted team developing exciting products in the Molecular Biology field for consumers and collaborate with cross-functional teams. Our team rewards intellectual curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the cutting edge of both academic and applied research in this product area, you have the opportunity to work together with some of the most talented scientists, engineers, and product managers.
RO, Bucharest
The Consumer Cloud Security (C2S) group is responsible for the protection of customer and corporate data. We are connected to all parts of Amazon's business and it’s massive, worldwide service-oriented architecture. We are starting the work on a new mission critical system that will preserve and improve the trusted experience that Amazon provides to its customers. This is a greenfield initiative with plenty of opportunity for innovation in the security space through new machine learning techniques.We are seeking a talented, self-directed Applied Scientist to work on the cutting edge security technologies. You'll design and run experiments, research new algorithms, and find new ways of protecting Amazon's customer trust. Besides theoretical analysis and innovation, you will work closely with talented engineers to put your algorithms and models into practice. You should thrive in ambiguous environments that require to find solutions to problems that have not been solved before. You enjoy and succeed in fast paced environments where learning new concepts quickly is a must. You leverage your exceptional technical expertise, a sound understanding of the fundamentals of Computer Science, and practical experience in building large-scale distributed systems. Your strong communication skills enable you to work effectively with both business and technical partners.Key responsibilities:· Process and analyze large data sets using as many techniques as necessary· Deliver scalable models that can analyze large data sets efficiently· Build mathematical models to detect and classify specific data elements with high accuracy· Prototype these models by using high-level modeling languages such as R or in software languages such as Python. A software team will be working with you to transform prototypes into production.· Create, enhance, and maintain technical documentation, and present to other scientists and business leaders.
IL, Tel Aviv
Join us in a historic endeavour 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.Location: Haifa and Tel aviv
US, WA, Seattle
Amazon is focused on protecting the health and safety of our employees while continuing to serve people who need our services more than ever. Regular testing on a global scale across all industries would both help keep people safe and help get the economy back up and running. But, for this to work, we as a society would need vastly more testing capacity than is currently available. Unfortunately, today we live in a world of scarcity where COVID-19 testing is heavily rationed. Until we have an effective vaccine available in billions of doses, high-volume testing capacity would be of great help, but getting that done will take collective action by NGOs, companies, and governments.The Role:We are a team of doers working passionately to apply cutting-edge advances in technology to solve real-world problems. As an Associate Scientist, you will work with a unique and gifted team developing exciting products for consumers and collaborate with cross-functional teams. Our team rewards intellectual curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the cutting edge of both academic and applied research in this product area, you have the opportunity to work together with some of the most talented scientists, engineers, and product managers.
US, CA, Palo Alto
Amazon Search team is responsible for the worldwide customer facing search features on desktops, tablets, and mobile devices – everything from the moment a customer clicks into the search box to when they view search results.As an Applied Science manager, you will lead the science innovation in search autocomplete and spelling corrections. Autocomplete accounts for half of all Search traffic on Amazon; spelling correction touches all searches. We touch the lives of hundreds of millions of Amazon customers every day. You will work with scientists and engineers to identify opportunities, solve the problems using data-driven algorithms and bring the solutions to production. You will help customers to better formulate their search queries and explore Amazon catalog through Autocomplete suggestions and enable customers to focus on their shopping mission, instead of spellings, by correcting their misspellings. You will also collaborate with Product, Design and Business functionalities to improve the usability of our features for all customer segments. All your work has a direct and visible impact on shopping experiences of Amazon customers.Joining this team, you’ll experience the benefits of working in a dynamic, entrepreneurial environment, while leveraging the resources of Amazon.com (AMZN), Earth's most customer-centric company.
UK, London
THIS ROLE IS FOR A 12-MONTH FIXED-TERM CONTRACTAmazon is seeking an outstanding Data Scientist on a 12 month fixed term contract to uncover key insights on how customers engage with Prime Video. As consumers increasingly consume digital video, we need to make agile decisions based on what content appeals most to our customers.You will have the following responsibilities within the scope of our global Prime Video business:- Support the analytical needs of the content acquisition management (CAM) team inclusive of statistical inferences, demand modelling, feature engineering and the bespoke evaluation of content licensing deals- Develop, maintain and improve on our predictive models for gauging global video content demand- Create new metrics and KPIs that effectively guide the business and deploy effective dashboards to surface them to senior leadership- Ensure that the quality and timeliness of analytic deliverables meet CAM expectations