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Rolf Neugebauer


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UK, Cambridge
“Alexa find me a job on the Alexa Knowledge team!”Our focus in the Alexa Knowledge team combines natural language understanding, acquiring large volumes of structured knowledge, and building autonomous machine reasoning to allow our customers to get answers to their questions in the most natural way possible. We’re part of a huge research and engineering effort on the Amazon Alexa team.We’ve solved many complex problems to get to where we are today, but there are still plenty of challenges ahead of us, and Alexa is getting smarter every day. The problems we solve in the Alexa Knowledge team in Cambridge help Alexa get smarter by understanding the different ways people talk, by learning more and more facts about the world, by improving her common sense reasoning and by responding in the most natural way possible in multiple languages. We set out to build Alexa at Amazon because we believe that voice will fundamentally improve the way people will interact with technology, and we wanted to create a computer that could be controlled entirely by your voice.On the Alexa Knowledge team, we are constantly making Alexa smarter by enabling her to learn about what’s going on in the world. We use many different techniques to enable learning and reasoning across a range of structured and unstructured data. We are constantly at the forefront of both research and engineering in understanding user demands and data sources, to extract the right knowledge, expand the range of, and how, Alexa accesses information – all to improve Alexa and give users the best experience. We believe that the information to answer (almost) every question can be found somewhere on the internet, and not just in an encyclopedia. Our goal is to teach Alexa how to autonomously consume a wider range of texts and expand her Knowledge Graph to learn more about the world.We use multiple Machine Learning and Natural Language Processing techniques to enable learning and reasoning across a range of structured data sources, at internet-level scale. This requires methods that lie beyond the cutting edge academic and industrial research of today. The scope of this role is broad, covering a diverse range of problem space that include, but are not limited to ontology expansion and alignment techniques, fact extraction from structured text, large-scale categorisation, supervised, weakly supervised or self-supervised learning methods etc. As a senior scientist, you will bring academic and/or industrial practical experience and create novel solutions to complex problems. You will guide junior scientists, collaborate with the best researchers in the field and work with the engineering team to bring your solutions to the millions of customers who use Alexa every day.
UK, Cambridge
“Alexa find me a job on the Alexa Knowledge team!”Our focus in the Alexa Knowledge team combines natural language understanding, acquiring large volumes of structured knowledge, and building autonomous machine reasoning to allow our customers to get answers to their questions in the most natural way possible. We’re part of a huge research and engineering effort on the Amazon Alexa team.We’ve solved many complex problems to get to where we are today, but there are still plenty of challenges ahead of us, and Alexa is getting smarter every day. The problems we solve in the Alexa Knowledge team in Cambridge help Alexa get smarter by understanding the different ways people talk, by learning more and more facts about the world, by improving her common sense reasoning and by responding in the most natural way possible in multiple languages. We set out to build Alexa at Amazon because we believe that voice will fundamentally improve the way people will interact with technology, and we wanted to create a computer that could be controlled entirely by your voice.On the Alexa Knowledge team, we are constantly making Alexa smarter by enabling her to learn about what’s going on in the world. We use many different techniques to enable learning and reasoning across a range of structured and unstructured data. We are constantly at the forefront of both research and engineering in understanding user demands and data sources, to extract the right knowledge, expand the range of, and how, Alexa accesses information – all to improve Alexa and give users the best experience. We believe that the information to answer (almost) every question can be found somewhere on the internet, and not just in an encyclopedia. Our goal is to teach Alexa how to autonomously consume a wider range of texts and expand her Knowledge Graph to learn more about the world.We use multiple Machine Learning and Natural Language Processing techniques to validate the information extracted from various structured and unstructured sources, at internet-level scale. This requires methods that lie beyond the cutting edge academic and industrial research of today. The scope of this role is broad, covering a diverse range of problem space that include, but are not limited to fact verification, natural language inference, large-scale categorisation, weakly supervised or self-supervised learning methods etc. As a senior scientist, you will bring academic and/or industrial practical experience and create novel solutions to complex problems. You will guide junior scientists, collaborate with the best researchers in the field and work with the engineering team to bring your solutions to the millions of customers who use Alexa every day.
US, TX, Austin
Have you ever ordered a product on Amazon and when that box with the smile arrives you wonder how it got to you so fast? Wondered where it came from and how much it would have cost Amazon? If so, Amazon’s Supply Chain Optimization Technologies (SCOT) team is for you.We build systems to peer into the future and estimate the distribution of tens of millions of products every week to Amazon’s warehouses in the most cost-effective way. When customers place orders, our systems use real time, large scale optimization techniques to optimally choose where to ship from and how to consolidate multiple orders so that customers get their shipments on time or faster with the lowest possible transportation costs. This team is focused on saving hundreds of millions of dollars using cutting edge science, machine learning, and scalable distributed software on the Cloud that automates and optimizes inventory and shipments to customers under the uncertainty of demand, pricing and supply.Watch this video to learn more about our organization, SCOT: http://bit.ly/amazon-scotIn S&OP we use cutting-edge machine learning and scalable distributed software in the Cloud to predict flows of products between our warehouses world-wide and distribute tens of millions of products every week in the most cost-effective way. We drive towards end to end automation solution requiring the use of machine learning in a wide variety of ways to forecasting, data anomaly detection, measuring the impact of our forecasts and bringing back this impact back to complete a closed loop process. You’ll have a WW impact in working with teams around the world in solving the unique challenges in each country that Amazon operates in.The Data Scientist, in partnership with the Product Management, Operations, and Tech teams will lead efforts in three areas:1) Building models to forecast inbound and outbound unit volumes through the world2) Identifying opportunities for forecast optimization by working with teams downstream to measure the results of or forecasts3) Evolve our anomaly detection efforts to ensure our automation efforts produce high quality results and issues are caught before the impact FC operations.Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation / Age
US, WA, Seattle
Are you an inventor interested in the latest research in machine learning and computer vision? Do you want to define the next generation of machine learning and computer vision algorithms? Do you wish you had access to large datasets? Answer yes to any of these questions and you’ll fit right in here at Amazon.HIT is a new group of seasoned scientists, engineers, product managers, and designers determined to redefine how our customers purchase products for their home. We believe that the objects that we choose to surround ourselves with have a huge impact on our quality of life. Not only they need to be useful, but they need to be beautiful, reflect our style, bring joy and make us proud.We are looking for a hands-on researcher, who is able to derive, implement, and test a large range of novel computer vision and machine learning algorithms. The research we do at HIT is innovative, multidisciplinary, and far-reaching. We aim to define, deploy, and publish cutting edge research.The ChallengeAs with every project within Amazon, we work backwards from our customer's needs and the challenges they have. Our team will tackle some of the toughest problems in retail.The technologyIn order to achieve our vision, we think big and tackle technology problems that are cutting edge. Where technology does not exist, we will built it. Where it exists we will need to modify it to make it work at Amazon scale. As the problem is so wide and the team new, we need members who are passionate and willing to learn:· Computer vision and machine learning. If you are passionate about these areas, join us.· Amazon scale systems. Our algorithms need to work at Amazon scale, serving hundreds of millions of customers with millisecond level latencies.· Big data & analytics. Amazon is data driven and a strong data backbone is necessary in our systems. We build upon core AWS services. If you are interested in gaining expertise, join us.· Personalization and machine learning. All technologies will be used in experiences adapted to what customers need, want or prefer.· Work on multiple platforms typically used in computer vision and machine learning research.Our Culture and YouWe are a tightly net group that share our experiences and help each other succeed. We believe in team work. We love hard problems and like to move fast in a growing and changing environment. We use data to guide our decisions and we always push the technology and process boundaries of what is feasible on behalf of our customers. The most successful members of our team are obsessed with helping our customers in creative ways, and bring clarity to ambiguity through data driven experimentation. If that sounds like an environment you like, join us.Major responsibilities:· Derive computer vision, machine learning, and analytical techniques for intelligent information retrieval/classification system to solve business problems.· Design, develop and deploy highly scalable computer vision and machine learning models.· Analyze and understand large amounts of Amazon’s historical business data.· Working closely with software engineering teams to build machine learning based features & products.· Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation, and model implementation.· Publish your work.· Mentor other engineers in the use of ML techniques.#hltech #hitech
US, WA, Seattle
Preserving Trust in Amazon with every customer, every transaction, every second is our mission. Our mission is to identify suspicious activity due to money laundering or terrorism financing and create investigations for humans to confirm and report to respective regulatory authorities, while supporting a best-in-class customer experience. We build automatic mechanisms to detect suspicious activities using a diverse set of algorithms and machine learning techniques. Amazon has hundreds of millions of customers, sellers, and developers all over the world that rely on Amazon products and services. We are handling massive scale. Amazon is one of a kind in the number of customers served, transactions processed, and products handled.Major responsibilities· Use statistical and machine learning techniques to create scalable risk management and support systems.· Analyze and understand large amounts of Amazon’s historical business data for specific instances of risk or broader risk trends.· Design, development and evaluation of highly innovative models for risk management.· Work closely with teams of scientists and software engineers to drive real-time model implementations and new feature creations.· Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.· Research and implement novel machine learning and statistical approaches.Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation
US, NY, New York
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
How often have you had an opportunity to be an early member of a team that is tasked with solving a huge customer need through disruptive, innovative technology, reinventing an industry?The Team: We are an internal facing team that is at the core of Amazon's Just Walk Out Technology that powers Amazon Go. Go introduces a new retail shopping paradigm with no lines and no checkout. You simply use the Amazon Go app to enter the store, take what you want from our selection of fresh, delicious meals and grocery essentials, and go. Our checkout-free shopping experience is made possible by the same types of technologies used in self-driving cars: computer vision, sensor fusion, and deep learning.The Role: As a Sr. Data Scientist, you will use a combination of outstanding data and analytical skills, leadership, thought clarity, cross-functional partnership, and strategic analysis to successful support the scaling of a tech operations team. You thrive on working with cutting-edge technology and have a strong understanding of business intelligence tools, operations optimization, and experience with ML/AI. Lastly, you deliver results in an ambiguous, fast-paced, dynamic business environment and are highly comfortable exercising fantastic judgment across a spectrum of highly diverse problems.
US, CA, Palo Alto
MULTIPLE POSITIONS AVAILABLEEntity: Amazon.com Services LLC, an Amazon.com CompanyTitle: Research Scientist IIWorksite: Palo Alto, CAPosition Responsibilities:Interact with various software and business groups to develop an understanding of their business requirements and operational processes. Utilize acquired knowledge and business judgment to build decision-supporting and operational tools to improve the bottom line. Build quantitative mathematical models to represent a wide range of supply chain, transportation and logistics systems. Implement these models and tools through the use of modeling languages and engineering code in software languages such as Java, C++, C# or C. Gather required data for analysis and mathematical model building by writing ad-hoc scripts and database queries. Perform quantitative, economic, and numerical performance analyses of these systems under uncertainty using statistical and optimization tools. Create computer simulations to support operational decision-making. Identify areas with potential for improvement and work with internal teams to generate requirements to realize improvements. Design optimal or near optimal solution methodologies to be used by in-house decision support tools and software. Create software prototypes to verify and validate the devised solutions methodologies. Integrate prototypes into production systems using standard software development tools and methodologies.Amazon.com is an Equal Opportunity-Affirmative Action Employer - Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.#0000
US, CA, Sunnyvale
Amazon Lab126 is an inventive research and development company that designs and engineer’s high-profile consumer electronics. Lab126 began in 2004 as a subsidiary of Amazon.com, Inc., originally creating the best-selling Kindle family of products. Since then, we have produced groundbreaking devices like Fire tablets, Fire TV and Amazon Echo. What will you help us create?Roles & ResponsibilitiesWe are looking for a passionate, talented and inventive Senior Applied Scientist in wireless to join our team. As part of the larger technology team working on new consumer technology, your work will have a large impact to hardware, internal software development, ecosystem, and ultimately the lives of Amazon customers. You must love building technologies & algorithms to deliver high quality wireless sensing & communication, and possess end-to-end expertise in signal processing and protocols. You must have a feel for what a good consumer experience should sound like.In your role, you will· Engage with an experienced cross-disciplinary staff to conceive and design innovative consumer products· Work closely with an internal inter-disciplinary team, and outside partners to drive key aspects of product definition, execution and test by making architecture-cost trade-offs decisions.· Develop and manage the roadmap, long-term vision and portfolio of new technology initiatives for the team· Create evaluation methods to track the actual performance of devised solutions in production systems, identify areas with potential for improvement and work with internal & external teams to improve the solution with new features· Improve, MAC, and link-layer scheduling algorithms· Be responsive, flexible and able to succeed within an open collaborative peer environment and provide technical and scientific guidance to your peers.· Communicate effectively with senior management as well as with colleagues from science, engineering, and business background· Integrate vendor hardware and software stacks· Mentor team members for their career development and growth
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.
US, WA, Seattle
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.
UK, MLN, Edinburgh
We’re looking for a machine learning scientist in the Personalization team for our Edinburgh office. You will be responsible for developing and disseminating customer-facing personalized recommendation algorithms. This is a hands-on role with global impact working with a team of world-class engineers and scientists across in the Edinburgh offices and wider organization.You will design algorithms that scale to very large quantities of data, and serve high-scale low-latency recommendations to all customers worldwide. You will embody scientific rigor, designing and executing experiments to demonstrate the technical efficacy and business value of your methods. You will also advocate for your approaches across Amazon and the research community, publishing and giving talks as well as leading business reviews. Your work delights customers by aiding in recommendations relevancy, and raise the profile of Amazon as a global leader in machine learning and personalization.Successful candidates will have strong technical ability, focus on customers by applying a customer-first approach, excellent teamwork and communication skills, and a motivation to achieve results in a fast-paced environment. Our position offers exceptional opportunities for every candidate to grow their technical and non-technical skills. If you are selected, you have the opportunity to make a difference to our business by designing and building state of the art machine learning systems on big data, leveraging Amazon’s vast computing resources (AWS), working on exciting and challenging projects, and delivering meaningful results to customers world-wide.Key responsibilities· Develop deep learning algorithms for high-scale recommendations problem· Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative analysis and business judgement.· Collaborate with software engineering teams to integrate successful experimental results into large-scale, highly complex Amazon production systems capable of handling 100,000s of transactions per second at low latency.· Report results in a manner which is both statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment.· Promote the culture of experimentation and science at Amazon.
US, WA, Seattle
Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by preventing eCommerce fraud? Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes 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? If yes, then you may be a great fit to join the Amazon Buyer Risk Prevention Machine Learning group.Major responsibilities· Use statistical and machine learning techniques to create scalable risk management systems· Analyzing and understanding large amounts of Amazon’s historical business data for specific instances of risk or broader risk trends· Design, development and evaluation of highly innovative models for risk management· Working closely with software engineering teams to drive real-time model implementations and new feature creations· Working closely with operations staff to optimize risk management operations,· Establishing scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation· Tracking general business activity and providing clear, compelling management reporting on a regular basis· Research and implement novel machine learning and statistical approaches
US, WA, Seattle
Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by preventing eCommerce fraud? Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes 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? If yes, then you may be a great fit to join the Amazon Buyer Risk Prevention Machine Learning group.Major responsibilities· Use statistical and machine learning techniques to create scalable risk management systems· Analyzing and understanding large amounts of Amazon’s historical business data for specific instances of risk or broader risk trends· Design, development and evaluation of highly innovative models for risk management· Working closely with software engineering teams to drive real-time model implementations and new feature creations· Working closely with operations staff to optimize risk management operations,· Establishing scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation· Tracking general business activity and providing clear, compelling management reporting on a regular basis· Research and implement novel machine learning and statistical approaches
US, VA, Herndon
The AWS Infrastructure Planning group is responsible for planning and coordinating a complex, multi-tier supply chain that's delivers capacity for all AWS services. This includes data center setup, equipment purchase, installation and operation of servers with power and cooling, inventory management and other such decisions.We're building a new suite of tools to automate all AWS supply chain planning, with a broad charter that involves inventory optimization, placement, vendor allocation, transition management, lead time predictions, and more. We are responsible for ensuring that the AWS cloud remains elastic for its customers by taking care of all of the back-end complexity, enabling our infrastructure to stay ahead of our rapid growth.We are looking for a high caliber Senior Manager who wants to solve some of the most challenging and interesting problems out there. If you want to stretch yourself with a high leverage, high impact role, this is it. The services that we own are responsible for billions of dollars in spend, resulting in us having a huge opportunity to move the needle in a positive direction. The team has a strong group of senior engineering, science, and product management talent, so it will be a great place for someone to deliver results, while also learning and progressing their career.
JP, 13, Meguro
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 has 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 leader to lead one of our international data science teams and develop a long-term roadmap for 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 leadership for our team of 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.Key responsibilities include:· Define, build, and lead a team of data scientists· Be the voice of analytics, support in-depth business reviews, and present to senior management.· Discover areas of the customer experience that can be automated through machine learning.· Partner with Product Management teams to drive requirements for new products and integrate data during product development.· Be a thought leader on data systems, data mining and analysis to scale our capabilities, uncover trends and develop insights.
US, MA, Cambridge
The Alexa Feedback organization owns a number of programs and domains which drive high customer engagement and feature discovery, maintains customer trust, understands customers’ feedback, develops new features that provide utility value for customers with special needs, and develops locally relevant experiences. The Alexa Experience Science team applies machine learning and natural language understanding algorithms to improve these programs and the functionality of domains such as News (“Alexa, What's the news?"), Feedback (“Alexa, that was wrong!"), Personality (“Alexa, what’s your favorite color?”), and to advance Alexa’s ability to handle more ambiguous utterances.We’re looking for a passionate, talented, and inventive Scientist to help build industry-leading ML technologies that help provide the best-possible experience for our customers. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to develop new features, predict key user behaviors and deliver automated decisions, both offline and in real time.
US, WA, Seattle
The Amazon Promise Economics Team in Supply Chain Optimization Technologies (SCOT) is hiring Interns in Economics. We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to work with large and complicated data sets. Knowledge of econometrics, as well as of Stata, R, or Python is necessary, and experience with SQL, UNIX, and Spark would be a plus.The Customer Promise team seeks to identify the optimal delivery option for whatever a customer wants. We believe that finding an optimal promise and living up to it consistently improves our customer experience because we increase customer's confidence and trust in Amazon as the one, best option to get what you want, when you want it.As the Economist for Customer Promise you will be responsible for leading the research, econometric modeling, and analysis to determine the optimal customer promise. This entails developing analytic tools and economic models that take into account inventory, fulfillment center capabilities, carrier capabilities, customer preferences, and economic impacts to determine customer promise. The models you develop will drive changes in transportation and fulfillment networks to ensure we are re providing customers with the fastest delivery experience while optimizing costs. These skills will also 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. Roughly 50% of research assistants from previous cohorts have converted to full time data science or economics employment at Amazon. If you are interested, please send your CV to our mailing list at econ-internship@amazon.com.Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation
US, WA, Seattle
Amazon Alexa Comunications (connecting people to family and friends) is looking for a Senior Applied Science Manager to lead the development of next generation Spoken Language Understanding, Recommendation, and other understanding and intelligent response systems that revolutionize multi-modal (voice and GUI) communication for Alexa's customers. In this role, you will manage teams of passionate, talented, and inventive scientists, to develop industry-leading natural language understanding (NLU), automatic speech recognition (ASR), recommendation, and other inference and response systems and drive them successfully to production for the benefit of millions of Alexa users. Your mission is to push the envelope in order to provide the industry-leading, best-possible experience for our customers.As a Senior Applied Science Manager, you will identify research directions, create roadmaps for forward-looking research and communicate them to senior leadership, and work closely with engineering teams to bring research to production. You will work with teams of talented scientists, and fill the ranks by attracting the best scientists in SLU, dialog and other Communication-related signal processing systems by representing Amazon Alexa at international science conferences. You will work with talented peers and leverage Amazon’s heterogeneous data sources and large-scale computing resources.
US, WA, Seattle
Prime Video is an industry leading, high-growth business and a critical driver of Amazon Prime subscriptions, which contribute to customer loyalty and lifetime value. Prime Video is a digital video streaming and download service that offers Amazon customers the ability to rent, purchase or subscribe to a huge catalog of videos. The Prime Video Economist team works on disruptive ideas in the Prime Video space.We are looking for a truly innovative Data Scientist to work on disruptive ideas within the Prime Video space. Examples of problem spaces you may be working on include video product pricing, ecosystem effects (how streaming affects rentals or purchases), and forecasting demand for new content on the platform. We also work on complex questions beyond video, for example how customers use and transition between Video and other digital products (e.g. Music or E-books/Audiobooks).In this role, you will build models that measure and predict the value that the business creates (or the value of new opportunities) for our customers. This role requires a team member with strong quantitative modeling skills and the ability to apply statistical/machine learning methods to large amount of individual level and title level data. The candidate should have strong communication skills, be able to work closely with stakeholders and translate data-driven findings into actionable insights. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail and ability to work in a fast-paced and ever-changing environment.On our team you will work with a diverse scientific team including engineers and economists as well as other data scientist to build statistical models using world-class data systems and partner directly with the business to implement the solutions.