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Harshavardhan Sundar


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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, CA, San Francisco
Can Alexa help anyone experience the music they enjoy? Even if they don't know what they'd like to listen to in this moment? Or, if they know they want “Happy rock from the 90s”, can she help them find it?Your machine learning skills can help make that a reality on the Amazon Music team. We are seeking an Applied Scientist who will join a team of experts in the field of machine learning, and work together to break new ground in the world of understanding and classifying different forms of music, and creating interactive experiences to help users find the music they are in the mood for. We work on machine learning problems for music classification, conversational AI, NLP, and music information retrieval.You'll work in a collaborative environment where you can pursue ambitious, long-term research, with many peta-bytes of data, work on problems that haven’t been solved before, quickly implement and deploy your algorithmic ideas at scale, understand whether they succeed via statistically relevant experiments across millions of customers, and publish your research. You'll see the work you do directly improve the experience of Amazon Music customers on Alexa/Echo, mobile, and web.The successful candidate will have a PhD in Computer Science with a strong focus on machine learning, or a related field, and 2+ years of practical experience applying ML to solve complex problems in signal processing, NLP or dialogue systems. Great if you have a passion for music, but this is not a requirement.Responsibilities:- Advance long-term, exploratory research projects in machine learning and related fields to create highly innovative customer experiences;- Analyze large amounts of Amazon’s customer data to discover patterns, find opportunities, and develop highly innovative, scalable algorithms to seize these opportunities;- Validate new or improved models via statistically relevant experiments across millions of customers;- Work closely with software engineering teams to build scalable prototypes for testing, and integrate successful models and algorithms in production systems at very large scale.Amazon MusicImagine being a part of an agile team where your ideas have the potential to reach millions. Picture working on cutting-edge consumer-facing products, where every single team member is a critical voice in the decision-making process. Envision being able to leverage the resources of a Fortune-500 company within the atmosphere of a start-up. Welcome to Amazon Music, where ideas are born and come to life as Amazon Music Unlimited, Prime Music, and so much more.Everyone on our team has a meaningful impact on product features, new directions in music streaming, and customer engagement. We are looking for new team members across a variety of job functions including software engineering/development, marketing, design, ops and more. Come join us as we make history by launching exciting new projects in the coming year.Our team is focused on building a personalized, curated, and seamless music experience. We want to help our customers discover up-and-coming artists, while also having access to their favorite established musicians. We build systems that are distributed on a large scale, spanning our music apps, web player, and voice-forward audio engagement on mobile and Amazon Echo devices, powered by Alexa to support our customer base. Amazon Music offerings are available in countries around the world, and our applications support our mission of delivering music to customers in new and exciting ways that enhance their day-to-day lives.Come innovate with the Amazon Music team!
CA, ON, Toronto
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.Fulfillment-by-Amazon (FBA) Inventory Optimization (FIO) is a relatively new team at Amazon’s Supply Chain Optimization Technologies (SCOT). We focus on driving long term free cash flow by automating and optimizing our third-party supply chain. The team’s efforts will address the key challenges facing the worldwide FBA Seller business, including 1) improving FBA Seller inventory efficiency, 2) efficiently balancing the supply and demand of FBA Seller capacity, 3) closing worldwide selection gap by enabling global selling profitability, and 4) driving out costs across the FBA supply chain to spin the flywheel. This is truly a unique problem space – optimizing for inventory in Amazon’s pipeline when you don’t control the process or own the inventory.FIO is seeking an Research Scientist to join its cross-functional team of data, applied and research scientists, economists, engineers, and product managers to utilize cutting edge optimization models, econometrics, machine-learning, and distributed software on the Cloud to build systems that automate and optimize inventory management under the uncertainty of demand, pricing and supply. We are recruiting a curious and creative Research Scientist who will collaborate with other scientists and engineers to leverage new machine learning methods and algorithms for the modeling and analysis of data.
US, WA, Seattle
At Amazon, we're working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people. Amazon is seeking a Sr Simulation and Innovation Engineer specialization in discrete event simulation and optimization of material process flow of complete Warehouse operations for our World Wide Design & Innovation Engineering Team. Amazon is one of the most recognizable brand names in the world and we distribute millions of products each year to our loyal customers.Responsibilities:· Lead system level complex Discrete Event Simulation (DES) projects to build , simulate, and optimize the fulfillment center operational process flow models using FlexSim, Demo 3D or any other Discrete Event Simulation (DES) software packages· Understand process flows , analyze data, perform Design of Experiments and effectively represent in simulation model to achieve better correlation and process improvements· Perform DES process flow simulations to design, build, and improve order fulfillment infrastructure throughout the large-scale supply chain network.· Manage multiple DES simulation projects and tasks simultaneously and effectively influence, negotiate, and communicate with internal and external business partners, contractors and vendors.Facilitate process improvement initiatives among site operations, engineering, and corporate systems groups.· Provide technical leadership for large-scale industrial engineering projects MS Excel, AutoCAD, and MS Projects.· Work with complex MHE and process design and influence multiple teams working closely with business teams to build consensus among discordant views· Lead and coordinate simulation and design efforts between internal teams and outside vendors to develop optimal solutions for the network, including equipment specification, material flow, process design, and site layout.· Deliver results according to project schedules and quality· Provide leadership and coordination between internal departments and vendors for multiple sites.· Develop design solutions to the best-in-class process flow to improve the throughput of the fulfillment facilities· Make technical trade-offs for long term/short-term needs considering challenges in business area by applying relevant data science disciplines, and interactions among systems.
US, WA, Seattle
Are you passionate about developing new state-of-the-art measurement approaches at Petabyte scale? Amazon Advertising is one of Amazon’s fastest growing businesses, and we are leveraging our unique data, the latest machine learning methods and big data technologies to better understand how advertising influences customer behavior. We are looking for an Applied Scientist to develop new systems and methods in the most challenging and data rich areas of marketing. We need an expert in experimental statistics, machine learning or causal inference to design advanced new models with our world class data systems.As part of the 1PM team, this role will partner with a dedicated engineering team measuring the impact Amazon's advertising and identifying opportunities for optimization at scale. We drive initiatives to make smarter marketing decisions and improve the relevance of advertising to our customers. We move away from industry standard measurement systems and build sophisticated and insightful decision engines. We enable massive advertising programs, generating billions of impressions with decorated with rich representations of customer state. The major challenges we are solving include integrating petabyte-scale distributed retail systems into a singular service to synthesize e-commerce data into measurement and optimization models. The successful candidate will have a causal inference background, a start-up mentality, an appreciation for white-space, and success solving problems with large data sets.Key responsibilities include:· Scientists at Amazon are expected to develop new techniques to process large data sets and contribute to design of automated systems.· Apply ML, statistics or econometrics knowledge to develop and analyze prototype models.· Design and analyze data from large-scale online experiments in order to validate prototype models.· Collaborate with scientists across teams in peer-review processes, publishing research in internal forms and industry conferences.· Partner closely with product and engineering teams to develop new measurement systems and translate prototype models to production.· Establish scalable, efficient, and automated processes for large scale model development, validation, and implementation.· Research and experiment with novel statistical modeling approaches.
US, WA, Seattle
In the Amazon Selection Monitoring team, we want Amazon to have a complete awareness of all products on earth. We aggregate and identify all products along with complete and accurate facts. Our goal is to enrich and increase the coverage of Amazon product selection guided by consumers’ interests. We are establishing the most comprehensive, accurate and fresh universal selection of products.We have multiple position for applied scientists who are excited to work in big data challenges including; web scale data integration, entity and product matching, improving data quality, natural language processing, discovery of new relationships along with its semantic, knowledge inferencing and enhancement to support strategic and tactical decision-making.We are looking for applied scientists with experience in building practical solutions and can work closely with software engineers to ship and automate solutions in production. Our applied scientist also collaborate and partner with other teams across Amazon to understand and reflect on how to create benefit for our customer.Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation / Age.
US, WA, Seattle
In the Amazon Selection Monitoring team, we want Amazon to have a complete awareness of all products on earth. We aggregate and identify all products along with complete and accurate facts. Our goal is to enrich and increase the coverage of Amazon product selection guided by consumers’ interests. We are establishing the most comprehensive, accurate and fresh universal selection of products.We have multiple position for applied scientists who are excited to work in big data challenges including; web scale data integration, entity and product matching, improving data quality, natural language processing, discovery of new relationships along with its sematic, knowledge inferencing and enhancement to support strategic and tactical decision-making.We are looking for applied scientists with experience in building practical solutions and can work closely with software engineers to ship and automate solutions in production. Our applied scientist also collaborate and partner with other teams across Amazon to understand and reflect on how to create benefit for our customer.Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation / Age.
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 provide a delightful experience to Amazon’s customers by pushing the envelope in Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), Machine Learning (ML), and Audio Signal Processing technologies.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.
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, 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
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, 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.