Abstract
We study the problem of semantic matching in product search, that is, given a customer query, retrieve all semantically related products from the catalog. Pure lexical matching via an inverted index falls short in this respect due to several factors: a) lack of understanding of hypernyms, synonyms, and antonyms, b) fragility to morphological variants (e.g. “woman" vs. “women"), and c) sensitivity to spelling errors. To address these issues, we train a deep learning model for semantic matching using customer behavior data. Much of the recent work on large-scale semantic search using deep learning focuses on ranking for web search. In contrast, semantic matching for product search presents several novel challenges, which we elucidate in this paper. We address these challenges by a) developing a new loss function that has an inbuilt threshold to differentiate between random negative examples, impressed but not purchased examples, and positive examples (purchased items), b) using average pooling in conjunction with n-grams to capture short-range linguistic patterns, c) using hashing to handle out of vocabulary tokens, and d) using a model parallel training architecture to scale across 8 GPUs. We present compelling offline results that demonstrate at least 4.7% improvement in Recall@100 and 14.5% improvement in mean average precision (MAP) over baseline stateof-the-art semantic search methods using the same tokenization method. Moreover, we present results and discuss learnings from online A/B tests which demonstrate the efficacy of our method.
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US, WA, Bellevue
Come join the Alexa team, building the speech and language solutions behind Amazon Echo and other Amazon products and services! You will help us invent the future.As a Data Scientist, you will design, evangelize, and implement state-of-the-art solutions for never-before-solved problems, helping Alexa to provide customer great products. This role will be a key member of a Alexa Data Service Science team based in Bellevue, WA. You will work closely with other research scientists, machine learning experts, engineers to design and run experiments, research new algorithms, and find new ways to improve Alexa Data Service products. You will partner with technology and product leaders to solve business and technology problems using scientific approaches to build new services that surprise and delight our customers. Our scientists work closely with software engineers to put algorithms into practice. They also work on cross-disciplinary efforts with other scientists within Amazon.The key responsibility for this role include:· Define proper output business Metrics, and build input models to identify patterns and drivers of the output.· Drive actions at scale using scientifically-based methods and decision making.· Design and develop complex mathematical, statistical, simulation and optimization models and apply them to define strategic and tactical needs and drive the appropriate business and technical solutions· Design experiments, test hypotheses, and build actionable models· Prototype these models by using modeling languages such as R or in software languages such as Python.· Work with software engineering teams to drive scalable, real-time implementations· Utilizing Amazon systems and tools to effectively work with terabytes of data
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US, MA, Cambridge
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US, MA, Boston
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US, WA, Bellevue
ML scientists at Amazon participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and time-series forecasting applications. Develop and/or apply statistical modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. Routinely build and deploy ML models on available data. Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists.The AWS Demand Forecasting and Planning team is responsible for growing the world's largest Cloud. We forecast customer demand, build ML systems that understand customer needs, and drive utilization improvement for all AWS services.What we own:· Building a world-class forecasting platform that scales to handling billions of time series data in real time.· Developing predictive customer analytics models and recommendation engines.· Expanding inventory replenishment models and systems for each AWS service in the fast-growing AWS product portfolio.· Finding out the optimal tradeoff between AWS service availability and fleet utilization.· Driving fleet utilization improvement where each 1% means tens of millions of additional free cash flow.· Automating tactical and strategic capacity planning tools to optimize for service availability and infrastructure cost.What you will learn:· State of the art forecasting methodologies.· Application of machine learning to large-scale customer analytics.· Inventory management and supply chain management for the Cloud.· Resource management and admission control for the Cloud.· The internals of all AWS services.Note that location is flexible between our Bellevue and Seattle offices.Keywords:Forecasting, Statistics, Machine Learning, Optimization, Inventory Management, Supply Chain Management, AWS, Cloud, Cloud Computing, EC2, S3, EBS, DynamoDB, CloudFront, Java, C++, Object Oriented, R, Distributed Systems, High Availability, Scalability, Concurrent
RO
The Amazon Devices team designs and engineers consumer electronics, including the best-selling Kindle family of products, Fire tablets, Fire TV, Amazon Dash, and Amazon Echo.As an Applied Scientist, you will participate in the design, development, and evaluation of models and machine learning (ML) technology to delight our customers.You will be part of a team delivering features that are well received by our customers.
RO
The Amazon Devices team designs and engineers consumer electronics, including the best-selling Kindle family of products, Fire tablets, Fire TV, Amazon Dash, and Amazon Echo.As an Applied Scientist, you will participate in the design, development, and evaluation of models and machine learning (ML) technology to delight our customers.You will be part of a team delivering features that are well received by our customers.
US, WA, Seattle
Workforce Staffing (WFS) supports Amazon Operations by hiring the hourly associates that staff our operational buildings. WFS is quickly becoming one of the world’s largest staffing organizations, forecasted to hire over one million hourly associates across North America and the European Union this year alone. Currently, we hire full time, part time, flex time and seasonal hires across Fulfillment Centers, Sort Centers, Amazon Logistics, Whole Foods, Amazon Air, Prime Now, Amazon Fresh, and emerging business lines. Interested in the businesses that Amazon creates and grows? Here’s your opportunity to be a part of this journey.The Workforce Intelligence team was created in 2018 to support the massive growth in scale and scope that WFS has experienced. The team has continued to grow rapidly in order to meet the expanding needs of the business, including: big data and machine learning solutions, innovative approaches to complex HR problems, and data-driven recommendations during a time of rapid change.Here’s where you come in:As a Research Scientist in Workforce Intelligence, your work is focused on research to deeply understand the people that make up our hourly workforce and help others do the same. You understand that even when hiring hundreds of thousands of hourly associates across multiple types of roles and businesses, the experience of each candidate matters.You use your deep expertise in surveys and statistics (regressions, multilevel models, etc.) to define and answer nebulous problems. You use experimental, quasi-experimental, and RCT methods to understand our candidates and influence critical business decisions. You relentlessly obsess over understanding our candidates and lead our survey program that seeks to amplify the voice of our candidates. You work with colleagues across Research, Data Science, Business Intelligence and related teams to enable Amazon find and hire the right candidates for the right roles at an unprecedented scale.This will be a highly visible role across multiple key deliverables for our global organization. If you are passionate and curious about data, obsess over customers, love questioning the status quo, and want to make the world a better place, let’s chat.
US, WA, Seattle
Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work.Please visit https://www.amazon.science for more information.At Alexa Shopping, we strive to enable shopping in everyday life. We allow customers to instantly order whatever they need, by simply interacting with their Smart Devices such as Amazon Show, Spot, Echo, Dot or Tap. Our Services allow you to shop, no matter where you are or what you are doing, you can go from 'I want that' to 'that's on the way' in a matter of seconds. We are seeking the industry's best to help us create new ways to interact, search and shop. Join us, and you'll be taking part in changing the future of everyday life.What you will do: You will lead a team of talented and experienced scientists and engineers that implement solutions for natural language understanding of Alexa Shopping customers: this involves taking the outputs from automated speech recognition (ASR) component and producing a representation of its meaning. Additionally, your team will build Alexa Shopping Automated CX quality metrics and provide analytics. This involves exploring, developing, socializing, and implementing mechanisms for tracking automated CX quality across customer’s journey with Alexa Shopping to improve Alexa Shopping CX. And finally, you will have the satisfaction of being able to look back and say you were a key contributor to something special from its earliest stages. You will be working closely with executive leadership, multiple product managers and leaders from partner teams in Amazon Retail, Alexa, and Speech Recognition teams.What we are looking for: We are looking for a talented Data Science Manager with a strong technical background and solid people management skills to build, manage and develop a highly-talented and experienced data science team. We are seeking leaders that can guide technical and product innovation in the areas of voice experiences, machine learning models and the distributed systems to bring our vision together. Strong judgment and communication skills, long term technical vision, and continuous focus on engineering and operational excellence are essential for the success in this role.
DE, BE, Berlin
As a Senior Applied Scientist on this growing team, you will take on a key role in improving the NLP and ranking capabilities of the Amazon product search engine. Our ultimate goal is to help customers find the products they are searching for, and discover new products they would be interested in. We do so by developing NLP components that cover a wide range of languages, not only English and major languages of Europe, but also Turkish, Arabic, Japanese, and more. The team plays a central role in search query understanding, product indexing, and representations/embeddings of queries and products, all of which aid in improving the ranking and relevance of search results.This is a rewarding role where you will be able to draw a clear connection between your work and how it improves the experience of millions of Amazon customers across the globe every day. You will propose and explore publication-worthy innovation in NLP and IR to build ML models trained on terabytes of product and traffic data, which are evaluated using both offline metrics as well as online metrics from A/B testing. You will then integrate these models into the production search engine that serves customers, closing the loop through data, modeling, application, and customer feedback. The chosen approaches for model architecture will balance business-defined performance metrics with the needs of millisecond response times.Your responsibilities include:· Analyze the data and metrics resulting from traffic into Amazon's product search service· Design, build, and deploy effective and innovative ML solutions to improve various components of the search stack, such as indexing, ranking, and query understanding· Evaluate the proposed solutions via offline benchmark tests as well as online A/B tests in production· Publish and present your work at internal and external scientific venues in the fields of ML/NLP/IRYour benefits include:· Working on a high-impact, high-visibility product, with your work improving the experience of millions of customers· The opportunity to use (and innovate) state-of-the-art ML methods to solve real-world problems· Being part of a growing team where you can influence the team's mission, direction, and how we achieve our goals· Excellent opportunities, and ample support, for career growth, development, and mentorship· Competitive compensation, including relocation support (for both domestic and international candidates)
US, WA, Seattle
Business/Team IntroductionThe Supply Chain Optimization Technologies (SCOT) team builds technology to automate and optimize Amazon’s supply chain of physical goods. We seek a Data Scientist with strong analytical and communication skills to join our team. SCOT manages Amazon's inventory under uncertainty of demand, pricing, promotions, supply, vendor lead times, and product life cycle. We optimize complex trade-offs between customer experience, inventory costs, fulfillment costs, fulfillment center capacity, etc. We develop sophisticated algorithms that involve learning from large amounts of data such as prices, promotions, similar products, and other data from our product catalog in order to automatically act on millions of dollars’ worth of inventory weekly and establish plans for tens of thousands of employees. As a Data Scientist, you will contribute to the research community, by working with other scientists across Amazon and our Supply Chain, as well as collaborating with academic researchers and publishing papers. SCOT also engages in cutting edge research that we try to share with the community. Recent work from SCOT includes papers presented at the NIPS 2017 Time Series Workshop, SSRN, KDD 2018 Time Series Workshop, and ICML 2018 Deep Generative Models Workshop.Data Scientist ResponsibilitiesAs a Data Scientist in SCOT, will be tasked to understand and work with bleeding edge research to enable the implementation of sophisticated models on big data. As a successful data scientist in the SCOT team, you are an analytical problem solver who enjoys diving into data from various businesses, is excited about investigations and algorithms, can multi-task, and can credibly interface between scientists, engineers and business stakeholders. Your expertise in synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication will enable you to answer specific business questions and innovate for the future.Major responsibilities include:· Analysis of large amounts of data from different parts of the supply chain and their associated business functions· Improving upon existing machine learning methodologies by developing new data sources, developing and testing model enhancements, running computational experiments, and fine-tuning model parameters for new models· Formalizing assumptions about how models are expected to behave, creating definitions of outliers, developing methods to systematically identify these outliers, and explaining why they are reasonable or identifying fixes for them· Communicating verbally and in writing to business customers with various levels of technical knowledge, educating them about our research, as well as sharing insights and recommendations· Utilizing code (Python, R, Scala, etc.) for analyzing data and building statistical and machine learning models and algorithms
US, WA, Seattle
Global Talent Management (GTM) is centrally responsible for creating and evolving Amazon’s human capital and talent programs and processes.People Science Team within GTM is a growing start-up team with direct impact on Amazonians across all of our businesses and locations around the world. We play a crucial role in ensuring top notch data products and insights facilitate our growth and development of talent in intelligent and curious ways. We regularly use data to pitch ideas and drive conversations with Amazon’s Senior Vice President of HR and other executives about how to improve existing talent programs to solve organizational problems focused on (but not limited to) talent differentiation, talent movement, employee-role matching, product integration, promotion practices, organization design and succession planning, and diversity and inclusion, or invent new ones that address the evolving needs of our diverse employee base.We are looking for a self-driven Economist to help shape analytics and research roadmap and enable data-driven innovation that fuel our rapidly scaling talent management mission. You will build econometric models, using our world class data systems, and apply economic theory to solve business problems in a fast moving environment. Economists at GTM will be expected to develop new techniques to process large data sets, apply a causal lens to the framework, address ambiguous business problems, and contribute to design of automated systems around the company.You will partner closely with product and program owners, as well as scientists and engineers from other disciplines (e.g. data science, software engineers, data engineering) with a clear path to business impact. You develop innovative and even frighteningly bold plans and ideas to discover new ways to advance our goals. You will be expected to be a thought leader as we chart new courses with our rapidly growing employee populations, and lead the way in experimenting new ideas that have not yet been explored.Key Responsibilities:· Participate in scoping and planning of GTM’s Science roadmap· Uncover drivers, impacts, and key influences on talent outcomes· Build new econometric models to improve existing talent products or those that make the case for new products· Bring a causal lens to questions in human resources employing either experiments or non-experimental approaches· Develop predictive and optimization models for key applications· Navigate a variety of data sources, such as enterprise data, customize surveys, focus groups, and/or external data sources· Ability to distill informal customer requirements into problem definitions, dealing with ambiguity and competing objectives· Work in expert cross-functional teams delivering on demanding projects
US, CA, Virtual Location - California
Amazon.com strives to be Earth's most customer-centric company where people can find and discover anything they want to buy online. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment.Economists at Amazon will be expected to work directly with senior management on key business problems faced in retail, international retail, cloud computing, third party merchants, search, Kindle, streaming video, and operations. Amazon economists will apply the frontier of economic thinking to market design, pricing, forecasting, program evaluation, online advertising and other areas. You will build econometric models, using our world class data systems, and apply economic theory to solve business problems in a fast moving environment. Economists at Amazon will be expected to develop new techniques to process large data sets, address quantitative problems, and contribute to design of automated systems around the company.
US, WA, Seattle
The AWS Central Economics team is looking for a PhD economist. The ideal candidate will have experience with time-series forecasting.You will learn about cloud products, including compute, storage, and databases. You will work on analytic projects requested by senior leadership. You will get the opportunity to learn new techniques. You will be a part of a team with many experienced economists.
US, VA, Arlington
Amazon’s Talent Assessment team designs and implements groundbreaking hiring solutions for one of the world’s fastest growing companies. We work in a fast-paced, global environment where we must solve complex problems (ranging from research-based to technical) and deliver solutions that have impact.We are seeking personnel selection researchers with a strong foundation in the development of pre-hire selection assessments, traditional and alternative legally defensible assessment validation approaches, research methodology, and data analysis. We are looking for equal parts researchers and consultant/thought leaders who are highly adaptable and continual learners who thrive in a fast paced environment.You will work closely with global teams to design and experiment new hiring solutions that predict success for highly complex roles (technical and non-technical) that have great impact on Amazon globally.What you’ll do:· Lead the tactical development and execution of large scale, highly visible personnel selection research projects· Develop and iterate on experimental research studies to optimize qualitative and quantitative hiring strategies· · Develop and innovate on new pre-hire test assessment design, validation, and implementation· · Partner with internal and external technology teams· Influence executive project sponsors and multiple business and development teams across the company· Drive effective teamwork, communication, and collaboration across multiple stakeholder groups
US, VA, Arlington
Amazon’s Talent Assessment team designs, implements, and optimizes hiring systems for one of the world’s fastest growing companies. We work in a data-focused, global environment solving complex problems with deep thought, large-sample research, and advanced quantitative methods to deliver practical solutions that make all aspects of hiring more fair, accurate, and efficient.We're looking for a curious data scientist interested in working on a multi-disciplinary team of applied scientists, psychologists, data engineers, business analysts, and program managers. In this role, you will apply your modeling skills to bust myths, create insights, and produce recommendations to help Amazon evaluate millions of potential new hires per year. You'll be involved in all phases of research and experiment design and analysis, including defining research questions, designing experiments, identifying data requirements, conducting statistical or machine learning-based modeling, and communicating insights and recommendations. You'll also be expected to continuously learn new systems, tools, and industry best practices to analyze big data and enhance our analytics.