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Washington, D.C.
Conference
KDD 2022
August 14 - 18, 2022
Washington, DC

Overview

The Knowledge Discovery and Data Mining Conference brings together researchers and practitioners from data science, data mining, knowledge discovery, large-scale data analytics, and big data.

Sponsorship Details

Gold
Conference website
Related research
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Amazon organizing committee members

Accepted publications

Workshops

KDD 2022 Workshop on Automation in Machine Learning
August 14 - August 17
Amazon workshop chairs: Jun (Luke) Huan, Tao Wang

Website: https://sites.google.com/view/automl2022-workshop
KDD 2022 Workshop on Mining and Learning with Graphs
August 15
The workshop serves as a forum for researchers from a variety of fields working on mining and learning from graphs to share and discuss their latest findings.

Amazon organizer: Shobeir Fakhraei

Website: http://www.mlgworkshop.org/2022
KDD 2022 Workshop on AI for Climate Mitigation, Adaptation, and Environmental Justice
August 15 - May 15
Since 2016, the Fragile Earth Workshop has brought together the research community to find and explore how data science can measure and progress climate and social issues, following the framework of the United Nations Sustainable Development Goals (SDGs).

Amazon organizer: Emre Eftelioglu

Website: https://ai4good.org/fragile-earth-2022
KDD 2022 Workshop on Misinformation and Misbehavior Mining on the Web & Making a Credible Web for Tomorrow
August 15
MIS2-TrueFact@KDD 2022 provides a venue for researchers and practitioners from academia, government and industry can share insights and identify new challenges and opportunities in adjacent to these diverse areas to coalesce around central and timely topics in online misinformation and misbehavior, resolving conflicts, fact-checking and ascertaining credibility of claims and present recent advances in research.

Amazon organizer: Mehran Kafai

Website: http://claws.cc.gatech.edu/mis2-truefact-kdd2022.html
KDD 2022 Workshop on Online and Adaptive Recommender Systems
August 15
The KDD workshop on online and adaptive recommender systems (OARS) will serve as a platform for publication and discussion of OARS. This workshop will bring together practitioners and researchers from academia and industry to discuss the challenges and approaches to implement OARS algorithms and systems, and improve user experiences by better modeling and responding to user intent.

Amazon organizer: Tao Ye

Website: https://oars-workshop.github.io/
Weighing dynamic availability and consumption for Twitch recommendations
Edgar Chen, Mark Ally, Eder Santana, Saad Ali
2022
Machine learning
KDD 2022 First Content Understanding and Generation for E-commerce Workshop
August 15 - May 2
Amazon program committee: Shaunak Mishra, Soumya Roy, Shilpa Ananth, Yashal Kanungo, Indraneil Paul, Bryan Wang, Yang Liu, Jinmiao Fu, Sameer Kanase

Amazon organizers: Sumit Negi, Rajdeep Banerjee, Manisha Verma, Pooja A

Website: https://content-generation.github.io/workshop
StFT: Style loss and Fourier transformation for domain gap reduction
Sarthak Srivastava, Khaleeque Ansari
2022
Computer vision
Machine learning attribution: Inferring item-level impact from slate recommendation in e-commerce
Shenghe Xu, Yan Zhao, Sameer Kanase, Mitchell Goodman, Saad Khan, Brent Payne, Patricia Grao
2022
Machine learning
KDD 2022 Workshop on Mining and Learning from Time Series – Deep Forecasting: Models, Interpretability, and Applications
August 15, 8:00 AM - May 15, 5:00 PM EDT
Amazon workshop organizers: Jun (Luke) Huan, Jan Gasthaus, Yuyang (Bernie) Wang, Hilaf Hasson, Youngsuk Park

Website: https://kdd-milets.github.io/milets2022/
Towards robust multivariate time-series forecasting: Adversarial attacks and defense mechanisms
Linbo Liu, Youngsuk Park, Trong Nghia Hoang, Hilaf Hasson, Jun Huan
2022
Machine learning
MQTransformer: Multi-horizon forecasts with context dependent attention and optimal bregman volatility
Kevin C. Chen, Lee Dicker, Carson Eisenach, Dhruv Madeka
2022
Machine learning
MQ-ReTCNN: Multi-horizon time series forecasting with retrieval-augmentation
Sitan Yang, Carson Eisenach, Dhruv Madeka
2022
Machine learning
Identifying and overcoming transformation bias in forecasting models
Sushant More
2022
Machine learning
Representation learning using a multi-branch transformer for industrial time series anomaly detection
Ruichuan Zhang, Fangzhou Cheng, Aparna Pandey
2022
Machine learning
KDD 2022 Cup ESCI Challenge for Improving Product Search
August 15
In this challenge, we introduce the “Shopping Queries Data Set”, a large dataset of difficult search queries, published with the aim of fostering research in the area of semantic matching of queries and products. The primary objective is to build new ranking strategies and, simultaneously, identify interesting categories of results (i.e., substitutes) that can be used to improve the customer experience when searching for products.

Amazon chair: Karthik Subbian

Amazon organizers: Lluis Marquez, Fran Valero, Nikhil Rao, Hugo Zaragoza, Sambaran Bandyopadhyay, Arnab Biswas, Anlu Xing, Chandan K Reddy

Website: https://www.aicrowd.com/challenges/esci-challenge-for-improving-product-search
KDD 2022 Workshop on Applied Machine Learning Management
August 15
The workshop on Applied Machine Learning Management brings together applied research managers from various fields to share methodologies and case-studies on management of ML teams, products, and projects, achieving business impact with advanced AI-methods.

Amazon organizer: Elena Sokolova

Amazon speaker: Shiv Vitaladevuni

Website: https://wamlm-kdd.github.io/2022
KDD 2022 Workshop on Anomaly and Novelty Detection, Explanation, and Accommodation (ANDEA)
August 15
This workshop will gather researchers and practitioners from diverse communities and knowledge background to promote the development of fundamental theories, effective algorithms, and novel applications of anomaly and novelty detection, characterization, and adaptation.

Amazon organizer: Anton van den Hengel

Website: https://sites.google.com/view/andea2022
One-class predictive autoencoder towards unsupervised anomaly detection on industrial time series
Hongjing Zhang, Fangzhou Cheng, Aparna Pandey
2022
Machine learning
KDD 2022 Workshop on Artificial Intelligence for Computational Advertising (AdKDD)
August 15
AdKDD 2022 is the leading workshop on artificial intelligence for computational advertising in conjunction with KDD 2022.

Amazon organizer: Kun Liu

Website:https://www.adkdd.org
Learning to bid with AuctionGym
Olivier Jeunen, Sean Murphy, Ben Allison
2022
Machine learning
KDD 2022 Workshop on AI-enabled Cybersecurity Analytics and Deployable Defense
August 15
This workshop aims to convene academics and practitioners (from industry and government) to share, disseminate, and communicate completed research papers, work in progress, and review articles about AI-enabled cybersecurity analytics and deployable AI-based security defenses.

Website: https://ai4cyber-kdd.com
Firenze: Model evaluation using weak signals
Bhavna Soman, Ali Torkamani, Mike Morais, Jeffrey Bickford, Baris Coskun
2022
Security, privacy, and abuse prevention
KDD 2022 Workshop on Decision Intelligence and Analytics for Online Marketplaces
August 15
The goal of this workshop is to offer an opportunity to appreciate the diversity in applications, to draw connections to inform decision optimization across different industries, and to discover new problems that are fundamental to marketplaces of different domains.

Amazon speaker: Rui Song

Website: https://sites.google.com/view/kdd22onlinemarketplaces

Tutorials

KDD 2022 Tutorial on Hyperbolic Neural Networks: Theory, Architectures and Applications
August 14, 1:00 PM - 5:00 PM EDT
The goal of this tutorial is to introduce researchers/practitioners to the fundamentals of hyperbolic geometry and explain the basic implementations of Hyperbolic models. We will describe the hyperbolic variants of the widely used deep learning architectures (such as GNNs, RNNs, and CNNs) and demonstrate their advantages over the standard Euclidean counterparts.

Amazon organizers: Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Srinivasan H. Sengamedu, and Chandan K. Reddy

Website: https://www.nurendra.me/hyperbolic-networks-tutorial
KDD 2022 Tutorial on Graph Neural Networks in Life Sciences
August 14, 1:00 PM - 5:00 PM EDT
Graphs are ubiquitous representation in life sciences and medicine. Recent advance in graph machine learning (ML) approaches such as graph neural networks (GNNs) has transformed a diverse set of problems relying on biomedical networks. The objective of this tutorial is twofold. First, it will provide a comprehensive overview of the types of biomedical graphs/networks, the underlying biological and medical problems, and the applications of graph ML algorithms for solving those problems. Second, it will showcase four concrete GNN solutions in life sciences with hands-on experience for the attendees.

Amazon organizers: Zichen Wang, Vassilis N. Ioannidis, Huzefa Rangwala, Tatsuya Arai, Ryan Brand, Mufei Li, Yohei Nakayama

Website: https://github.com/dglai/Graph-Neural-Networks-in-Life-Sciences

Related content

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Applied Scientist- AWS AI
US, CA, Santa Clara
Job summaryAmazon is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help build industry-leading language technology.Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Processing (NLP), Natural Language Understanding (NLU), Dialog management, conversational AI and Machine Learning (ML).As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services, as well as contributing to the wider research community. You will gain hands on experience with Amazon’s heterogeneous text and structured data sources, and large-scale computing resources to accelerate advances in language understanding.We are hiring primarily in Conversational AI / Dialog System Development areas: NLP, NLU, Dialog Management, NLG.This role can be based in NYC, Seattle or Palo Alto.Inclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
Applied Scientist- AWS AI
US, NY, New York
Job summaryAmazon is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help build industry-leading language technology.Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Processing (NLP), Natural Language Understanding (NLU), Dialog management, conversational AI and Machine Learning (ML).As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services, as well as contributing to the wider research community. You will gain hands on experience with Amazon’s heterogeneous text and structured data sources, and large-scale computing resources to accelerate advances in language understanding.We are hiring primarily in Conversational AI / Dialog System Development areas: NLP, NLU, Dialog Management, NLG.This role can be based in NYC, Seattle or Palo Alto.Inclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
Research Scientist II, Funnel Science and Analytics
US, WA, Seattle
Job summaryWorkforce Staffing (WFS) brings together the workforce powering Amazon’s ability to delight customers: the Amazon Associate. With over 1M hires, WFS supports sourcing, hiring, and developing the best talent to work in our fulfillment centers, sortation centers, delivery stations, shopping sites, Prime Air locations, and more.WFS' Funnel Science and Analytics team is looking for a Research Scientist. This individual will be responsible for conducting experiments and evaluating the impact of interventions when conducting experiments is not feasible. The perfect candidate will have the applied experience and the theoretical knowledge of policy evaluation and conducting field studies.Key job responsibilitiesAs a Research Scientist (RS), you will do causal inference, design studies and experiments, leverage data science workflows, build predictive models, conduct simulations, create visualizations, and influence science and analytics practice across the organization.Provide insights by analyzing historical data from databases (Redshift, SQL Server, Oracle DW, and Salesforce).Identify useful research avenues for increasing candidate conversion, test, and create well written documents to communicate to technical and non-technical audiences.About the teamFunnel Science and Analytics team finds ways to maximize the conversion and early retention of every candidate who wants to be an Amazon Associate. By focusing on our candidates, we improve candidate and business outcomes, and Amazon takes a step closer to being Earth’s Best Employer.
Applied Scientist, AI Research & Education
US, CA, Santa Clara
Job summaryAWS AI/ML is looking for world class scientists and engineers to join its AI Research and Education group working on building automated ML solutions for planetary-scale sustainability and geospatial applications. Our team's mission is to develop ready-to-use and automated solutions that solve important sustainability and geospatial problems. We live in a time wherein geospatial data, such as climate, agricultural crop yield, weather, landcover, etc., has become ubiquitous. Cloud computing has made it easy to gather and process the data that describes the earth system and are generated by satellites, mobile devices, and IoT devices. Our vision is to bring the best ML/AI algorithms to solve practical environmental and sustainability-related R&D problems at scale. Building these solutions require a solid foundation in machine learning infrastructure and deep learning technologies. The team specializes in developing popular open source software libraries like AutoGluon, GluonCV, GluonNLP, DGL, Apache/MXNet (incubating). Our strategy is to bring the best of ML based automation to the geospatial and sustainability area.We are seeking an experienced Applied Scientist for the team. This is a role that combines science knowledge (around machine learning, computer vision, earth science), technical strength, and product focus. It will be your job to develop ML system and solutions and work closely with the engineering team to ship them to our customers. You will interact closely with our customers and with the academic and research communities. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. You are also expected to work closely with other applied scientists and demonstrate Amazon Leadership Principles (https://www.amazon.jobs/en/principles). Strong technical skills and experience with machine learning and computer vision are required. Experience working with earth science, mapping, and geospatial data is a plus. Our customers are extremely technical and the solutions we build for them are strongly coupled to technical feasibility.About the teamInclusive Team CultureAt AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded scientist and enable them to take on more complex tasks in the future.Interested in this role? Reach out to the recruiting team with questions or apply directly via amazon.jobs.
Applied Scientist, AI Research & Education
US, CA, Santa Clara
Job summaryAWS AI/ML is looking for world class scientists and engineers to join its AI Research and Education group working on building automated ML solutions for planetary-scale sustainability and geospatial applications. Our team's mission is to develop ready-to-use and automated solutions that solve important sustainability and geospatial problems. We live in a time wherein geospatial data, such as climate, agricultural crop yield, weather, landcover, etc., has become ubiquitous. Cloud computing has made it easy to gather and process the data that describes the earth system and are generated by satellites, mobile devices, and IoT devices. Our vision is to bring the best ML/AI algorithms to solve practical environmental and sustainability-related R&D problems at scale. Building these solutions require a solid foundation in machine learning infrastructure and deep learning technologies. The team specializes in developing popular open source software libraries like AutoGluon, GluonCV, GluonNLP, DGL, Apache/MXNet (incubating). Our strategy is to bring the best of ML based automation to the geospatial and sustainability area.We are seeking an experienced Applied Scientist for the team. This is a role that combines science knowledge (around machine learning, computer vision, earth science), technical strength, and product focus. It will be your job to develop ML system and solutions and work closely with the engineering team to ship them to our customers. You will interact closely with our customers and with the academic and research communities. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. You are also expected to work closely with other applied scientists and demonstrate Amazon Leadership Principles (https://www.amazon.jobs/en/principles). Strong technical skills and experience with machine learning and computer vision are required. Experience working with earth science, mapping, and geospatial data is a plus. Our customers are extremely technical and the solutions we build for them are strongly coupled to technical feasibility.About the teamInclusive Team CultureAt AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded scientist and enable them to take on more complex tasks in the future.Interested in this role? Reach out to the recruiting team with questions or apply directly via amazon.jobs.
Senior Applied Scientist - Machine Learning, Personalization, Recommendations, Machine Learning, Causal Inference, Personalization
US, WA, Seattle
Job summaryHow can we create a rich, data-driven shopping experience on Amazon? How do we build data models that helps us innovate different ways to enhance customer experience? How do we combine the world's greatest online shopping dataset with Amazon's computing power to create models that deeply understand our customers? Recommendations at Amazon is a way to help customers discover products. Our team's stated mission is to "grow each customer’s relationship with Amazon by leveraging our deep understanding of them to provide relevant and timely product, program, and content recommendations". We strive to better understand how customers shop on Amazon (and elsewhere) and build recommendations models to streamline customers' shopping experience by showing the right products at the right time. Understanding the complexities of customers' shopping needs and helping them explore the depth and breadth of Amazon's catalog is a challenge we take on every day. Using Amazon’s large-scale computing resources you will ask research questions about customer behavior, build models to generate recommendations, and run these models directly on the retail website. You will participate in the Amazon ML community and mentor Applied Scientists and software development engineers with a strong interest in and knowledge of ML. Your work will directly benefit customers and the retail business and you will measure the impact using scientific tools. We are looking for passionate, hard-working, and talented Applied scientist who have experience building mission critical, high volume applications that customers love. You will have an enormous opportunity to make a large impact on the design, architecture, and implementation of cutting edge products used every day, by people you know.Key job responsibilitiesScaling state of the art techniques to Amazon-scaleWorking independently and collaborating with SDEs to deploy models to productionDeveloping long-term roadmaps for the team's scientific agendaDesigning experiments to measure business impact of the team's effortsMentoring scientists in the departmentContributing back to the machine learning science community
Applied Scientist
US, NY, New York City
Job summaryAmazon Web Services is looking for world class scientists to join the Security Analytics and AI Research team within AWS Security Services. This group is entrusted with researching and developing core data mining and machine learning algorithms for various AWS security services like GuardDuty (https://aws.amazon.com/guardduty/) and Macie (https://aws.amazon.com/macie/). In this group, you will invent and implement innovative solutions for never-before-solved problems. If you have passion for security and experience with large scale machine learning problems, this will be an exciting opportunity.The AWS Security Services team builds technologies that help customers strengthen their security posture and better meet security requirements in the AWS Cloud. The team interacts with security researchers to codify our own learnings and best practices and make them available for customers. We are building massively scalable and globally distributed security systems to power next generation services.Inclusive Team Culture Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Work/Life Balance Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives. Mentorship & Career Growth Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign projects based on what will help each team member develop and enable them to take on more complex tasks in the future.A day in the lifeAbout the hiring groupJob responsibilities* Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative and business judgment.* Collaborate with software engineering teams to integrate successful experiments into large scale, highly complex production services.* Report results in a scientifically rigorous way.* Interact with security engineers, product managers and related domain experts to dive deep into the types of challenges that we need innovative solutions for.
Applied Scientist, Alexa AI
US, WA, Bellevue
Job summary Do you want to join Alexa AI -- the science team behind Amazon’s intelligence voice assistance system? Do you want to utilize cutting-edge deep-learning and machine learning algorithms to delight millions of Alexa users around the world? If your answers to these questions are “yes”, then come join us at the Alexa Artificial Intelligence (AI) team, which is in charge of improving Alexa user satisfaction through real-time metrics monitoring and continuous closed-loop learning. The team owns the modules that reduce user perceived defects and frictions through utterance reformulation, contextual and personalized hypothesis ranking. Key job responsibilitiesThe Alexa AI team is interested in an Applied Scientist to work alongside a team of experienced machine/deep learning scientists and engineers. The ideal Candidate will create data driven machine learning models and solutions on tasks such as sequence-to-sequence query reformulation, graph feature embedding, personalized ranking, etc..Additional responsibilities include: Analyze, understand, and model user-behavior and the user-experience based on large scale data, to detect key factors causing satisfaction and dissatisfaction (SAT/DSAT)Build and measure novel online & offline metrics for personal digital assistants and user scenarios, on diverse devices and endpointsCreate and innovate deep learning and/or machine learning based algorithms for utterance reformulation and contextual hypothesis ranking to reduce user dissatisfaction in various scenariosPerform model/data analysis and monitor user-experienced based metrics through online A/B testingResearch and implement novel machine learning and deep learning algorithms and models
Manager, Data Sciences, Physical Stores BI
US, CA, Santa Clara
Job summaryAmazon is looking for a customer focused, analytically and technically skilled Data Sciences Leader for Amazon Physical Stores Business. We’re trying to optimize shopping experience for Amazon’s Customers in the Physical retail space. This role will be a key member of the core Analytics team, based in Seattle, WA. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, an ability to work in a fast-paced, high-energy and ever-changing environment. The drive and capability to shape the business group strategy is a must.In this role, you will work to establish world class data science, analytics and reporting for Amazonians as part of building the Physical Retail experience for our customers. This key role will work closely with internal partners to assist in developing and managing analytic solutions. Your team will work closely with Product Managers, Software Engineers, and Program Managers to develop statistical models, design and run experiments, and find new ways to optimize customer shopping and product experience. You and your team will influence the direction of the business by leveraging our data to deliver insights that drive decisions and actions. The role will involve translating broad business problems into specific analytics projects, conducting deep quantitative analyses, and communicating results effectively. We see a high potential for influence and growth in this role as we transform our data into actionable insights to continue to fuel the growth of this business. Key job responsibilities• Manage a team of data scientists, identify opportunities and develop data science strategies.• Translate business questions and concerns into specific analytical questions that can be answered with available data using statistical methods.• Apply Statistical and Machine Learning methods to specific business problems and data.• Ensure data quality throughout all stages of acquisition and processing, including such areas as data sourcing/collection, ground truth generation, normalization, transformation, cross-lingual alignment/mapping, etc.• Communicate proposals and results in a clear manner backed by data and coupled with actionable conclusions to drive business decisions.• Collaborate with colleagues from multidisciplinary science, engineering and business backgrounds.• Work with engineers to develop efficient data querying and modeling infrastructure.• Manage your own process. Prioritize and execute on high impact projects, triage external requests, and ensure to deliver projects in time.• Utilizing code (Python, R, Scala, etc.) for analyzing data and building statistical models.
Data Scientist - Nationwide Opportunities, AWS Professional Services
US, NC, Virtual Location - N Carolina
Job summaryWant to help the largest global enterprises derive business value through the adoption of Artificial Intelligence (AI) and Machine Learning (ML)? Excited by using massive amounts of disparate data to develop ML models? Eager to learn to apply ML to a diverse array of enterprise use cases? Thrilled to be a part of Amazon who has been pioneering and shaping the world’s AI/ML technology for decades? At Amazon Web Services (AWS), we are helping large enterprises build ML models on the AWS Cloud. We are applying predictive technology to large volumes of data and against a wide spectrum of problems. AWS Professional Services works together with AWS customers to address their business needs using AI solutions. AWS Professional Services is a unique consulting team. We pride ourselves on being customer obsessed and highly focused on the AI enablement of our customers. If you have experience with AI, including building ML models, we’d like to have you join our team. You will get to work with an innovative company, with great teammates, and have a lot of fun helping our customers. A successful candidate will be a person who enjoys diving deep into data, doing analysis, discovering root causes, and designing long-term solutions. Major responsibilities include:Assist customers by being able to deliver a ML project from beginning to end, including understanding the business need, aggregating data, exploring data, building & validating predictive models, and deploying completed models with concept-drift monitoring and retraining to deliver business impact to the organizationUse AWS AI services (e.g., Personalize), ML platforms (SageMaker), and frameworks (e.g., MXNet, TensorFlow, PyTorch, SparkML, scikit-learn) to help our customers build ML modelsResearch and implement novel ML approaches, including hardware optimizations on platforms such as AWS InferentiaWork with our other Professional Services consultants (Big Data, IoT, HPC) to analyze, extract, normalize, and label relevant data, and with our Professional Services engineers to operationalize customers’ models after they are prototypedInclusive Team Culture Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching 85,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Work/Life Balance Our team puts a high value on work-life harmony. Striking a healthy balance between your personal and professional life is crucial to your happiness and success here. We are a customer-obsessed organization—leaders start with the customer and work backwards. They work vigorously to earn and keep customer trust. As such, this is a customer facing role in a hybrid delivery model. Project engagements include remote delivery methods and onsite engagement that will include travel to customer locations as needed. Mentorship & Career Growth Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future. This is a customer-facing role and you will be required to travel to client locations and deliver professional services as needed.This position requires the candidate selected be a US citizen because it provides services under a federal government contract with clearance requirements. This position is limited to individuals who can obtain and maintain the federal government clearance required by the contract.In compliance with the U.S. government requirement that employees of its contractors receive the COVID-19 vaccine if those employees work on or in connection with U.S. government contracts, this position may require that the candidate selected be fully vaccinated against COVID-19. A person is considered fully vaccinated by completing the full regimen of the COVID-19 vaccine (two doses for Pfizer or Moderna and one dose for Johnson & Johnson).
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