Seattle

Amazon is a place where data drives most of our decision-making. Alexa Enterprise team is looking for a dynamic data engineer who can be innovative, a strong problem solver and can lead the implementation of the analytical data infrastructure that will guide decision making. As a Data Engineer, you think like an entrepreneur, constantly innovating and driving positive change, but more importantly, you consistently deliver mind-boggling results. You're a leader, who uses both quantitative and qualitative methods to get things done. And on top of it all, you're someone who wonders "What if?" and then seeks out the solution. This position offers exceptional opportunities to grow your technical and non-technical skills. You have the opportunity to really make a difference to our business by inventing, enhancing and building world class systems, delivering results, working on exciting and challenging projects.As a Data Engineer, you are responsible for analyzing large amounts of business data, solving real world problems, and developing metrics and business cases that will enable us to continually delight our customers worldwide. This is done by leveraging data from various platforms such as Jira, Portal, Salesforce. You will work with a team of Product Managers, Software Engineers and Business Intelligence Engineers to automate and scale the analysis, and to make the data more actionable to manage business at scale. You will own many large datasets, implement new data pipelines that feed into or from critical data systems at Amazon.You must be able to prioritize and work well in an environment with competing demands. Successful candidates will bring strong technical abilities combined with a passion for delivering results for customers, internal and external. This role requires a high degree of ownership and a drive to solve some of the most challenging data and analytic problems in retail. Candidates must have demonstrated ability to manage large-scale data modeling projects, identify requirements and tools, build data warehousing solutions that are explainable and scalable. In addition to the technical skills, a successful candidate will possess strong written and verbal communication skills and a high intellectual curiosity with ability to learn new concepts/frameworks and technology rapidly as changes arise.Key job responsibilities - Design, implement and support an analytical data infrastructure - Manage AWS resources including EC2, EMR, S3, Glue, Redshift, etc. - Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL and AWS big data technologies - Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency - Collaborate with Data Scientists and Business Intelligence Engineers (BIEs) to recognize and help adopt best practices in reporting and analysis - Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers - Maintain internal reporting platforms/tools including troubleshooting and development. Interact with internal users to establish and clarify requirements in order to develop report specifications. - Work with Engineering partners to help shape and implement the development of BI infrastructure including Data Warehousing, reporting and analytics platforms. - Contribute to the development of the BI tools, skills, culture and impact. - Write advanced SQL queries and Python code to develop solutionsA day in the lifeThis role requires you to live at the intersection of data, software, and analytics. We leverage a comprehensive suite of AWS technologies, with key tools including S3, Redshift, DynamoDB, Lambda, API's, Glue. You will drive the development process from design to release. Managing data ingestion from heterogeneous data sources, with automated data quality checks.Creating scalable data models for effective data processing, storage, retrieval, and archiving.Using scripting for automation and tool development, which is scalable, reusable, and maintainable.Providing infrastructure for self serve analytics and science use cases.Using industry best practices in building CI/CD pipelinesAbout the teamThe Alexa Enterprise (AE) mission is to extend Alexa's capabilities and services to partners, accelerating Alexa's vision of creating the smartest, most capable and trusted AI personal assistant. We help our partners create value, and deliver a business we love. Our business mission is focused towards the following areas:1) Distribute Alexa across 3P endpoints such as smart TVs and speaker profitably drive incremental endpoints and new-to-Alexa customer acquisition2) Bring value to customers in hotels, senior living communities, and healthcare properties3) Offer branded conversational AI assistants to partners4) Ensure product certification, quality checks, and developer support to partnersWe serve world-class customers across the industry. Our products have been featured in publications such as CNET and Forbes, and Amazon has celebrated our progress in its quarterly earnings highlights. Our vision is for Alexa to become an integral part of our enterprise customers, driving revenue, lowering costs, and improving end user satisfaction. Our team values work-life harmony and a diversity of lifestyles and family schedulesBASIC QUALIFICATIONS- 3+ years of data engineering experience- Experience with data modeling, warehousing and building ETL pipelines- Experience with SQL ...

Amazon is seeking a candidate that is passionate about leveraging data to deliver actionable insight that impacts business decisions to improve the customer experience within the Global Customer Service Concessions Team. The Global Concessions Team focuses on systematically identifying and eliminating defects leading to returns and egregious experiences for customers across different marketplaces. We do this through regional programs and working with resolver teams around the world. In Concessions we embrace our differences and are committed to furthering our culture of inclusion. We do this by attracting, developing, and retaining amazing talent from diverse backgrounds. We are looking for an individual who is curious, motivated, and able to work effectively with diverse peers; someone who will amplify the positive and inclusive team culture we’ve been building.Key job responsibilitiesAs a Data Engineer, the ideal candidate will partner with Software Developers, Business Intelligence (BI) Engineers, Scientists, and Program Managers to develop scalable and maintainable data pipelines on both structured and unstructured (text based) data. This candidate should have strong business judgment, a good sense of architectural design, written/documentation skills, and experience with big data technologies (Spark/Hive, Redshift, EMR, + Other AWS technologies). This role involves overseeing existing pipelines as well as developing brand new ones for reporting and data warehousing. The operating environment is fast paced and dynamic, however has a strong team spirit and welcoming culture. To thrive, the ideal candidate must be detail oriented, enthusiastic and flexible, and in return they will gain tremendous experience with the latest big data technologies as well as exposure (as desired) to statistical and Natural Language modeling through collaboration with scientists on global issue detection models and development.A day in the lifeA successful Data Engineer will be highly collaborative and organized, capable of prioritizing multiple deliverables, and effective at communicating progress and blockers. This candidate should feel comfortable working across multiple data-sources and be capable of participating in and understanding how multiple systems communicate information to one another.If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) PlanAbout the teamWe are a group that has fun at work, cares about the impact of our products, and is not just focused on the bottom line. Our growing team has the rare opportunity of directly impacting the customer experience by generating insights that improve supply chain efficiencies. We are backed by a strong leadership group dedicated to operational excellence that empowers a reasonable work-life balance. As an established, experienced team, we offer the scope and support needed to achieve substantial career growth. Come join us and innovate with the Amazon Stores Customer Services, Concessions BI Team!BASIC QUALIFICATIONS- 3+ years of data engineering experience- Experience with data modeling, warehousing and building ETL pipelines- Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)- Experience in building pipeline in Apache Air flow or similar tools.- Experience with one or more scripting language (e.g., Python, KornShell)- Bachelor's Degree ...

Innovation is at the core of what we do. We believe that by removing and reducing the barriers thatprevent people from taking their medications, we can help customers conveniently get the medications they need, when they need them and take them as prescribed. We have provided customers with the ability to find transparent and simple pricing, receive 24/7 customer service support, and have their meds delivered to their doorsteps while creating programs and products that embody our mission and position ourselves in becoming the world’s safest and fastest online pharmacy.We are looking for a Data Engineer to join us on our journey to make it drastically easier for customers to find, choose, afford, and engage with the services, products, and professionals they need to get and stay healthy!As a Data Engineer in Pharmacy team, you will partner with Software Engineers, Business Intelligence Engineers and product managers. In close collaboration with the Sr. Data Engineer on the team, you will design, implement, and maintain next generation BI solutions for large scale, highly secure and complex data structures to ensure the data is auditable, available and accessible. You will gain a deep understanding of our services and the data they produce, and become our resident expert in how to transform that data into a format that is useful for analytics and business intelligence. You will proactively help to identify new data for integration with our platform, and propose and implement new technologies to help us better understand our data.#everydaybetterKey job responsibilities• Design, implement, maintain and support a secure and robust data lake in native AWS with 300+ datasets which contain both PII and PHI data.• Implement ingestion routines both real time and batch using best practices in modeling, ETL/ELTprocesses by leveraging AWS technologies and big data tools.• Interface with other technology teams to extract, transform, and load data from a wide varietyof data sources using SQL, Python and AWS big data technologies.• Gather business and functional requirements and translate into secure, robust, scalable, operable solutions with a flexible and adaptable architecture.• Collaborate with engineers to help adopt best practices in system creation, integrity, test design,analysis, validation, and documentation.• Help continually improve ongoing reporting and analysis processes, automating or simplifyingself-service tools for customers.• Explore and learn the latest AWS technologies to provide new capabilities and increaseefficiency.About the teamInnovation is at the core of what we do. We believe that by removing and reducing the barriers that prevent people from taking their medications, we can help customers conveniently get the medications they need, when they need them and take them as prescribed.We have provided customers with theability to find transparent and simple pricing, receive 24/7 customer service support, and have their meds delivered to their doorsteps while creating programs and products that embody our mission and position ourselves in becoming the world’s safest and fastest online pharmacy.We are looking for a Data Engineer to join us on our journey to make it drastically easier for customers to find, choose, afford, and engage with the services, products, and professionals they need to get and stay healthy!As a Data Engineer in Pharmacy team, you will partner with Software Engineers, Business Intelligence Engineers and product managers. In close collaboration with the Sr. Data Engineer on the team, you will design, implement, and maintain next generation BI solutions for large scale, highly secure and complex data structures to ensure the data is auditable, available and accessible. You will gain a deep understanding of our services and the data they produce, and become our resident expert in how to transform that data into a format that is useful for analytics and business intelligence. You will proactively help to identify new data for integration with our platform, and propose and implement new technologies to help us better understand our data.BASIC QUALIFICATIONS- Experience with data modeling, warehousing and building ETL pipelines- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR- 3+ years of data engineering experience- Experience with Redshift, Oracle, NoSQL etc.- Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field- Experience in working and delivering end-to-end projects independently.- Excellent written and verbal communication skills Amazon is committed to a diverse and inclusive workplace. ...

Come build a brand-new data architecture environment from scratch in the Merchant Fulfilled Network (MFN) team within the Customer Service (CS) organization to support robust reports, machine learning (ML) models, and complex data analysis.We are looking for an experienced Data Engineer who thrives in an ambiguous environment and is able to create foundational solutions that will sustain the scale of a rapidly growing team. The ideal candidate should be highly analytical, thorough, and an organized self-starter.As a Data Engineer on the team, this candidate will be creating a data warehouse architecture from the ground up and help it mature to support high-volume data related to Buyers, Sellers, Concessions Attribution, as well as Buyer/Seller Abuse and Seller Experience.Candidate should excel at designing, creating, managing, and customizing large datasets to meet business use cases. This candidate should have excellent business and technical communication skills to be able to work with business owners to develop and define key business questions, and to build data pipelines, integration engineering, Machine Learning workflows, and automation solutions that answer those questions.This role requires an individual with excellent problem-solving skills, expertise in working with streaming data, deep knowledge of data pipeline engineering using AWS data technologies, a strong understanding of business intelligence solutions, and familiarity with how machine learning models work.Candidate will primarily be responsible for setting up a robust data warehouse platform, designing and implementing complex ETL pipelines in the data warehouse platform and other business intelligence (BI) solutions to support the rapidly growing and dynamic business demand for data, and use it to deliver the data as a service, which will have an immediate influence on day-to-day decision-making at Amazon. This candidate will also be responsible for designing andimplementing deployment dependencies for ML models, including feature engineering, model hosting, and integration mechanisms.Key job responsibilities- Build the infrastructure to answer questions with data, using software engineering best practices, data management fundamentals, data storage principles, and recent advances in distributed systems- Partner with Research Scientists and Software Development Engineers to evolve, optimize and integrate ML models into the broader Customer Service platform to drive and innovate contact experience for customers- Help drive the architecture and technology choices that enable a world-class user experience- Manage AWS resources- Uphold Operational Excellence best practices in Data Engineering and actively contribute to evolve set standards.- Collaborate with Business Intelligence Engineers (BIEs) to recognize and help adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation- Develop expertise in a broad range of Amazon’s data resources and know when, how, and which to use and which not to use- Encourage the organization to adopt next-generation data architecture strategies, proposing both data flows and storage solutions- Present your findings to large groups of technical and non-technical (business side) audience.A day in the lifeEmbark on an exciting journey to build a data infrastructure from the ground up, empowering the MFN and Buyer/Seller Abuse prevention teams to reach new heights!As a Data Engineer, you will have the unique opportunity to architect a robust, scalable data ecosystem using the latest AWS technologies. Leverage agile methodologies to create sustainable, innovative solutions that will drive business growth and deliver real-time insights to decision-makers.If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:1. Medical, Dental, and Vision Coverage2. Maternity and Parental Leave Options3. Paid Time Off (PTO)4. 401(k) PlanAbout the teamThe Analytics team is a dynamic, cross-functional group working within a rapidly growing organization. While relatively new, we are highly skilled and passionate about driving data-powered innovation.If you thrive in a fast-paced, collaborative environment and are eager to contribute to the development of transformative data capabilities, we encourage you to apply. Together, let's elevate our data maturity and deliver meaningful business outcomes.BASIC QUALIFICATIONS- Bachelor's degree- 5+ years of data engineering experience- Experience as a data engineer or related specialty (e.g., software engineer, business intelligence engineer, data scientist) with a track record of manipulating, processing, and extracting value from large datasets- Experience with data modeling, warehousing and building ETL pipelines ...

Do you enjoy problem-solving and using data to analyze information on a grand scale? Are you passionate about manipulating data to tackle complex internal and external customer problems and improve business results? Do you want to be a part of a fast-paced environment and contribute to one of the most visited sites on the Internet?At Amazon, we hire the best minds in technology to innovate on behalf of our customers. The focus we have on our customers is why we are one of the world’s most beloved brands – customer obsession is part of our company DNA. Data engineers use technology to solve complex problems and get to see the impact of their work first-hand.The challenges data engineers solve for at Amazon are big and impact millions of customers, sellers, and products around the world. Our path is not always simple, so we are selective about who joins us on this journey. There is a certain kind of person who takes on this role at Amazon – someone who is excited by the idea of creating new products, features, and services from scratch while managing ambiguity and the pace of a company whose ship cycles are measured in weeks, not years.Come chart your own path at Amazon.Note: By applying to this position, your application will be considered for all locations we hire for in the United States including but not limited to: Seattle/Bellevue, WA; Nashville, TN; Austin, TX; Greater Bay Area, CA; DC Metro Area; Denver, CO; Detroit, MI; Greater Boston Area, MA; Greater Denver Area, CO; Greater Los Angeles Area, CA; Greater New York Area; Irvine, CA; Madison, WI; Minneapolis, MN; Phoenix, AZ; Portland, OR; San Diego, CA.As a data engineer, you will/may: Design, implement, and automate deployment of our distributed system for collecting and processing log events from multiple sources Design data schema and operate internal data warehouses and SQL/NoSQL database systems Own the design, development, and maintenance of ongoing metrics, reports, analyses, and dashboards to drive key business decisions Monitor and troubleshoot operational or data issues in the data pipelines Drive architectural plans and implementation for future data storage, reporting, and analytic solutions Work collaboratively with business analysts, data scientists, and other internal partners to identify opportunities/problems Provide assistance to the team with troubleshooting, researching the root cause, and thoroughly resolving defects in the event of a problemAbout the teamUtility Computing (UC)AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for customers who require specialized security solutions for their cloud services.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. 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 that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future.Diverse ExperiencesAWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.About AWSAmazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.Inclusive Team CultureHere at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.Work/Life BalanceWe value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.Mentorship & Career GrowthWe’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.BASIC QUALIFICATIONS- 1+ years of data engineering experience- Experience with data modeling, warehousing and building ETL pipelines- Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)- Experience with one or more scripting language (e.g., Python, KornShell) ...

AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help. You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.As a Data Engineer you will enable data-driven decision making within the Amazon Web Services Data Center Infrastructure Operations organization. The Infrastructure Operations Team is responsible for planning, implementing, monitoring and continuously improving the global Amazon Data Center infrastructure. The team supports all aspects of the Data Center based organizations, including but not limited to : Safety, Security, maintenance, daily operations, logistics, engineering and equipment management.You will be developing, implementing and maintaining the information data lake and utilizing insight platforms to enable decision support systems for the overall organization. You should have excellent business and communication skills, and be able to work with business owners to understand their data and reporting requirements.Above all, you should be passionate about working with huge data sets and be someone who is able to bring data sets together to answer business questions and drive growth. You will build ETLs to ingest the data into the data warehouse and data lake, as well as end-user facing reporting applications. You will primarily support teams within the Infrastructure environment, but will also have opportunities to support teams in the overall Amazon Web Services community.You will work with business customers and development teams to define analytics requirements and then deliver flexible, scalable, end-to-end solutions.You will have an opportunity to work with big data and emerging technologies while driving business intelligence solutions end-to-end: business requirements, data modeling, ETL, metadata, reporting, and dashboarding. You should have expertise in the design, creation, management, and business use of large datasets.About the teamThe Central Infrastructure Analytics Team (CIAT). We are a team of engineers and scientists committed to providing accurate, actionable data and insights that support business decisions within Infrastructure Operations.We provide unified data sources and business intelligence solutions to the Infrastructure Operations (InfraOps) global teams. We obsess over providing low-latency, accurate, actionable data to customers throughout AWS, accomplished through self-service data access, subscription-based reporting, and comprehensive analyses. We lead the business with predictive and prescriptive analyses providing our partners the insights and the anticipatory forecasting they need to deliver best in class services to our customers, promoting cost reduction, increased sustainability, and overall efficiency.CIAT are responsible for the sourcing, centralizing, preparing and vending both raw data and processed data/reports, to our customers across all aspects of AWS and Data Center Operations. We differ from other central teams as our remit is both cross functional and function specific depending on the individual customer requirements. We are uniquely positioned to provide an integrated perspective based on the available data feeds. We continually expand our data sources to maintain alignment with the changing business systems and requirements of our customers. We actively engage with our partner teams to grow our business knowledge so that our developed solutions reflect the collective knowledge gained through our partnerships. We are responsible for the data quality and security, ensuring that the vended data subscribes to Amazons least privilege and business need-to-know ethos. We support direct access to >4400 data tables across >360 schemas, developed and manage >390 reports within >75 dashboards, and provide direct report and data access to >5000 unique users across AWS. Through the development and transition to LakeSQL, CIAT have enabled the user-manager access to >300 additional datalakes, via OMNI, removing CIAT data transfer pipelines as a user data access constraint. Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. BASIC QUALIFICATIONS- 5+ years of data engineering experience- Experience with data modeling, warehousing and building ETL pipelines- Experience with SQL- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS- Experience mentoring team members on best practices ...

Operations Finance Technology team, responsible for building technical solutions for multi-billion WW Operational Cost analytic including Inbound cost (Receiving / PO), variable Cost, fixed cost, outbound (Customer Shipments / Transportation), and Customer Service, is looking for a Data Engineer. As a data engineer, you will get the exciting opportunity to work on very large data sets in one of the world's largest and most complex data warehouse environments. You will work closely with the business teams in analysis on various cost savings initiatives, many non-standard and unique business problems and use creative-problem solving to deliver actionable output. You will be responsible for designing and implementing an analytical environment using third-party and in-house reporting tools, modeling metadata, building reports and dashboards. You will have an opportunity to work with leading edge technologies like Redshift, Hadoop/Hive/Pig. You will be writing scalable queries and tuning performance on queries running over billion of rows of data. BASIC QUALIFICATIONS- 3+ years of data engineering experience- Experience with data modeling, warehousing and building ETL pipelines ...

Are you interested in building high-performance and globally scalable reporting and analytics infrastructure that support Amazon's Global Real Estate and Facilities (GREF) organization’s current and future growth? Are you seeking an environment where you can drive innovation leveraging the scalability and innovation with Amazon's AWS cloud services? Do you have a passion for ensuring a positive customer experience? This is the opportunity for you.In Finance Automation, we built technology to simplify and automate the processes Amazon uses to manage its financial relationships with external stakeholders. We are on a journey to create technology that simplifies the processes that Amazon uses to procure, collect and pay. We recently formed a new GREF Technology team which is the software development team for GREF. This team builds products and tools to enable Amazon’s corporate real estate team as they build and operate the company’s facilities worldwide.The GREF Tech team is looking for a passionate, solution-oriented Data Engineer to lead the implementation of the analytical data infrastructure that will guide the decision making behind initiatives such as space planning, design and construction, corporate security, travel, transportation, lease, facilities, and other key projects within the Global Real Estate and Facilities (GREF) domain. The team is committed to building the next generation reporting and analytics platform to support Amazon's rapidly growing workforce and improve employee experience. Our projects span multiple organizations and require coordination of data integrity, test design, analysis, validation, and documentation. - You will act as the business-facing subject matter expert for data storage and feature instrumentation, with the responsibility of managing end-to-end execution and delivery across various work streams. - You will help drive data architecture across many large datasets, perform exploratory data analysis, implement new data pipelines that feed into or from critical data systems at Amazon. - You will be responsible for designing and implementing scalable ETL processes in the AWS platform to support the rapidly growing and dynamic business demand for data, and use it to deliver the data as service which will have an immediate influence on day-to-day decision making and strategic initiatives. - You will hold a highly visible role that requires interaction with leaders across Finance Automation and GREF.- You will provide technical leadership on high-impact cross-functional initiatives BASIC QUALIFICATIONS- 3+ years of data engineering experience- Experience with data modeling, warehousing and building ETL pipelines- Experience with SQL- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS- Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR ...

The Amazon Devices organization designs, produces and markets Kindle e-readers, Fire Tablets, Fire TV Streaming Media Players and Echo Speakers, and is constantly looking to innovate on behalf of customers with new devices in existing or new categories or improving the customer experience on existing platforms. The Devices Analytics team provides customer engagement support to the broader organization for Kindle, Fire, and Echo products – established and emerging countries, worldwide. We are looking for an innovative, hands-on and customer-obsessed Data Engineer who can be a strategic partner to the product managers and engineers on the team. Our projects span multiple organizations and require coordination of experimentation, economic and causal analysis, forecasting, and predictive machine learning tools. You will act as the business-facing subject matter expert for data storage, feature instrumentation, and data privacy, with the responsibility of managing end-to-end execution and delivery across projects. In this role, you will be a technical expert with massive impact. You work tightly with the research scientist and business intelligence engineers on our team to create the data infrastructure and pipelines to drive our machine learning projects from initial experimentation to production level deployment. Your work will directly impact the success of Amazon's growing Devices business. You will work across diverse science/engineering/business teams. You will work on critical data engineering problems, building unique high quality reliable, accurate, consistent, and architecturally sound data sets that are aligned with our business needs.Key Performance Areas - Design, implement and support an analytical data infrastructure - Managing AWS resources including EC2, EMR, S3, Glue, Redshift, etc. - Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL and AWS big data technologies - Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency - Collaborate with Data Scientists and Business Intelligence Engineers (BIEs) to recognize and help adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation - Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customersBASIC QUALIFICATIONS- 3+ years of data engineering experience- Experience with data modeling, warehousing and building ETL pipelines- Experience with SQL ...

Do you love working with data? Are you excited about handling a lot of data? Do you want to make new tools that make it easy to get information from data? Are you keen on solving problems that no other company has solved?In this role, you will sit with the GTMC SIERRA's engineering organization, and work with Data Engineers, Software developer engineers, UX designers, business intelligence engineers and data scientists. You will be responsible to design and build data products and services at scale to have a significant impact on 1.5 million Amazonians and the communities Amazon serves.As a Data Engineer II, you should be an expert with data lake fundamentals around storage, compute, etc., familiar with multiple data processing stacks like Spark, EMR, and core data concepts (e.g. Data Modeling and Reporting). You should have deep understanding of the architecture for enterprise level data lake/mesh solutions using NAWS stack or other cloud stacks. You should be an expert in the design, creation, management, and business use of large data-sets. The candidate is expected to be able to build efficient, flexible, extensible, and scalable ETL and reporting solutions. You should be enthusiastic about learning new technologies and be able to implement solutions using them to provide new functionality to the users or to scale the existing platform. Our ideal candidate thrives in a fast-paced environment, relishes working with large transactional volumes and big data, enjoys the challenge of highly complex business contexts (that are typically being defined in real-time), and, above all, is a passionate about data and analytics.Key job responsibilitiesDesign, implement, and support a platform providing secured access to large datasets.Architect , develop and maintain end to end scalable data infrastructure and data pipelines.Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL, scripting and AWS big data technologies. Designing and implementing complex ETL pipelines and other BI solutions.Work closely with business owners, developers, Business Intelligence Engineers to explore new data sources and deliver the data.Keep up to date with advances in big data technologies and run pilots to design the data architecture to scale with the increased data volume using AWS.Empower the team for self-servicing by providing the necessary skills to handle complex tasks independently. Ensure that the team can efficiently manage and troubleshoot data-related issues, leading to increased autonomy and productivity. along with fostering a culture of self-reliance.About the teamGlobal Talent Management & Compensation (GTMC) SIERRA (Science, Insights, Experience, Research, Reporting & Analytics) is a horizontal, multi-disciplinary organization whose mission is to be a force multiplier for the broader GTMC organization and our key customer cohorts. We accomplish this by using our expertise in data analytics and science, economics, machine learning (ML), UX, I/O psychology, and engineering to build insights and experiences that raise the bar in understanding and shaping decision making at scale by integrating within and across talent journeys as well as through self-service tools and closed loop mechanisms outside of those journeys. Our portfolio of products spans foundational data sources, metrics, and research through to finished features and products that our end-customers interact with on a daily basis.BASIC QUALIFICATIONS- 1+ years of data engineering experience- Experience with data modeling, warehousing and building ETL pipelines- Experience with SQL- Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)- Experience with one or more scripting language (e.g., Python, KornShell) ...

"We see our customers as invited guests to a party, and we are the hosts. It's our job every day to make every important aspect of the customer experience a little bit better." - Jeff Bezos, Founder & CEO. We didn’t make Amazon a multi-billion-dollar company, our customers did and we want to ensure that our customers always have a positive experience that keeps them coming back to Amazon. To help achieve this, the Worldwide Defect Elimination (WWDE) team relentlessly focuses on maintaining customer trust by building products that offer appropriate resolutions to resolve issues faced by our customers. WWDE engineers solve complex problems and build scalable, cutting-edge solutions to help our customers navigate through issues and eliminate systemic defects to prevent future issues. As a Data Engineer, the ideal candidate will partner with Software Developers, Business Intelligence Engineers, Scientists, and Program Managers to develop scalable and maintainable data pipelines on both structured and unstructured (text based) data. This candidate should have strong business judgment, good sense of architectural design, written/documentation skills, and experience with big data technologies (Spark/Hive, Redshift, EMR, +Other AWS technologies). This role involves both overseeing existing pipelines as well as developing brand new ones for ML. The operating environment is fast paced and dynamic, however has a strong team spirited and welcoming culture. To thrive, the ideal candidate must be detail oriented, enthusiastic and flexible, in return they will gain tremendous experience with the latest in big data technologies as well as exposure (as desired) to statistical and Natural Language modeling through collaboration with scientists on global issue detection models and development.A day in the lifeIf you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:1. Medical, Dental, and Vision Coverage2. Maternity and Parental Leave Options3. Paid Time Off (PTO)4. 401(k) PlanBASIC QUALIFICATIONS- 1+ years of data engineering experience- Experience with data modeling, warehousing and building ETL pipelines- Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)- Experience with one or more scripting language (e.g., Python, KornShell)- Bachelor's Degree ...

WorldWide Amazon Stores FinTech (WWASFT) team is looking for an outstanding Data Engineer who is data-driven, uncompromisingly detail oriented, smart, efficient, and driven to help our business succeed. You have passion for technology. You are keen to leverage existing skills while trying new approaches. You are not tool-centric; you determine what technology works best for the problem at hand and apply it accordingly. You can explain complex concepts to your non-technical customers in simple terms.As a Data Engineer, you will be working in one of the world's largest and most complex data warehouse environments. You will design, implement and support scalable data infrastructure solutions to integrate with multi heterogeneous data sources, aggregate and retrieve data in a fast and safe mode, curate data that can be used in reporting, analysis, machine learning models and ad-hoc data requests. You will be exposed to cutting edge AWS big data technologies. You should have excellent business and communication skills to be able to work with business owners and Tech leaders to gather infrastructure requirements, design data infrastructure, build up data pipelines and data-sets to meet business needs. You stay abreast of emerging technologies, investigating and implementing where appropriate.Key job responsibilities- Design and develop the pipelines required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, Python and AWS big data technologies.- Oversee and continually improve production operations, including optimizing data delivery, re-designing infrastructure for greater scalability, code deployments, bug fixes and overall release management and coordination. - Establish and maintain best practices for the design, development and support of data integration solutions, including documentation.- Work closely with Product teams, Finance Teams, Software developers and Business Intelligence Engineer to explore new data sources and deliver the data.- Able to read, write, and debug data processing and orchestration code written Python/Scala etc following best coding standards (e.g. version controlled, code reviewed, etc.)BASIC QUALIFICATIONS- 3+ years of data engineering experience- Experience with data modeling, warehousing and building ETL pipelines- Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS ...

The Data Science Manager in Natural Language Processing (NLP) within the Customer Engagement Technology, Self-Service and Automation team will work on the research, design, and implementation of solutions to key challenges in developing, evaluating, and deploying solutions based on large pre-trained language models into conversational Artificial Intelligence (AI) systems that can understand and communicate with customers in a natural and contextually appropriate manner.This involves model development in areas such as multi-turn dialogue management, knowledge grounding, and open-ended generation and assessment of dialogue quality and style of the conversational model.Key job responsibilities- Lead a data science team to accelerate the development and deployment of chatbot scaling. This team will play a pivotal role in optimizing Human-in-the-Loop (HITL) tasks.- Implement state-of-the-art Natural Language Processing (NLP) and Machine Learning (ML) models for tasks such as language understanding, dialogue management, and response generation and dialogue quality assessment.- Collaborate with cross-functional teams, including applied scientists, software engineers, and product managers, to integrate Large Language Model (LLM)-based solutions into Amazon's customer service platforms.- Develop and implement strategies for data collection, annotation, and model training to ensure high-quality and robust performance of the chatbots.- Conduct experiments and evaluations to measure the performance of the developed models and systems, and identify areas for improvement.- Stay up-to-date with the latest advancements in NLP, LLMs, and conversational AI, and explore opportunities to incorporate new techniques and technologies into Amazon's customer service solutions.A day in the lifeWe thrive on solving challenging problems to innovate for our customers. By pushing the boundaries of technology, we create unparalleled experiences that enable us to rapidly adapt in a dynamic environment. Our decisions are guided by data, and we collaborate with engineering, science, and product teams to foster an innovative learning environmentIf you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!Benefits Summary:Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:1. Medical, Dental, and Vision Coverage2. Maternity and Parental Leave Options3. Paid Time Off (PTO)4. 401(k) PlanAbout the teamJoin our team of scientists and engineers who develop and deploy Large Language Model (LLM)-based solutions systems to enhance Amazon's customer service experience and effectiveness. We work on innovative solutions that help customers solve their issues and get their questions answered efficiently, and associate-facing products that support our customer service associate workforce.BASIC QUALIFICATIONS- 5+ years of building quantitative solutions as a scientist or science manager experience- 2+ years of scientists or machine learning engineers management experience- Ph.D. in computer science, mathematics, statistics, machine learning or equivalent quantitative field- Knowledge of Python or R or other scripting language- Experience working with scientists, economists, software developers, or product managers- 5+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience- Experience applying theoretical models in an applied environment ...

Come be a part of a rapidly expanding $35 billion-dollar global business. At Amazon Business, a fast-growing startup passionate about building solutions, we set out every day to innovate and disrupt the status quo. We stand at the intersection of tech & retail in the B2B space developing innovative purchasing and procurement solutions to help businesses and organizations thrive. At Amazon Business, we strive to be the most recognized and preferred strategic partner for smart business buying. Bring your insight, imagination and a healthy disregard for the impossible. Join us in building and celebrating the value of Amazon Business to buyers and sellers of all sizes and industries. Unlock your career potential.Amazon Business Data Insights and Analytics team is looking for a Data Scientist to lead the research and thought leadership to drive our data and insights strategy for Amazon Business. This role is central in shaping the definition and execution of the long-term strategy for Amazon Business. You will be responsible for researching, experimenting and analyzing predictive and optimization models. You will work on ambiguous and complex business and research science problems with large opportunities. You are an analytical individual who is comfortable working with cross-functional teams and systems. You must be a self-starter and be able to learn on the go. Excellent written and verbal communication skills are required as you will work very closely with diverse teams.Key job responsibilities- Interact with business and software teams to understand their business requirements and operational processes- Frame business problems into scalable solutions- Adapt existing and invent new techniques for solutions- Gather data required for analysis and model building- Create and track accuracy and performance metrics- Prototype models by using high-level modeling languages such as R or in software languages such as Python. - Familiarity with transforming prototypes to production is preferred.- Create, enhance, and maintain technical documentationBASIC QUALIFICATIONS- 2+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience- 2+ years of data scientist experience- 2+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience- Experience applying theoretical models in an applied environment ...

AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help. You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.In 2019, Amazon co-founded The Climate Pledge and made a commitment to achieve net-zero carbon by 2040 —10 years ahead of the Paris Agreement. We invited others to join us and there are now more than 300 businesses and organizations across 51 industries and 29 countries that have signed the Pledge, which means we are collectively coming at the climate crisis from nearly every sector and nearly every angle.As part of our efforts to decarbonize our business, we became the world’s largest corporate purchaser of renewable energy in 2020, and last year, we reached 85% renewable energy across our business, and are on a path to power our operations with 100% renewable energy by 2025.We recently announced that AWS will be water positive by 2030, returning more water to communities than it uses in its direct operations. The company also announced its 2021 global water use efficiency (WUE) metric of 0.25 liters of water per kilowatt-hour, demonstrating AWS’s leadership in water efficiency among cloud providers. To learn more about AWS’s water+ commitment visit: Water Stewardship.Come join the team that is building the tools and innovative technology to manage our growing portfolio of renewable energy investments, including solar, on-shore and off-shore wind farms.Key job responsibilitiesAs an data scientist, you will employ machine learning and analytics to create scalable solutions for problems in sustainable energy space. You will dissect large historical business data sets to enhance and streamline essential processes. You will partner with data and software teams to create models for predictive insights and establish automated methods for large data analysis.A day in the lifeTo learn more, you can visit: amazon sustainability in the cloudAbout the teamWhy AWSAmazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.Diverse ExperiencesAmazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.Work/Life BalanceWe value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.Inclusive Team CultureHere at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.Mentorship and Career GrowthWe’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.BASIC QUALIFICATIONS- 2+ years of data scientist experience- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience- Experience applying theoretical models in an applied environment ...

The Data Scientist in NLP within Customer Engagement Tech, Self-Service and Automation team will work on the research, design, and implementation of solutions to key challenges in developing, evaluating and deploying solutions based on large pretrained language models into conversational AI systems that can understand and communicate with customers in a natural and contextually appropriate manner. This involves model development in areas such as multi-turn dialogue management, knowledge grounding, and open-ended generation and assessment of dialogue quality and style of the conversational model.Key job responsibilities• Define and implement robust HITL strategies to effectively expedite LLM models scaling process.• Collaborate with human annotators and subject matter experts to establish clear guidelines and quality control measures.• Analyze feedback loops and iterate on model performance to ensure continuous improvement.• Conduct in-depth analysis of large-scale conversational datasets to identify patterns, trends, and potential challenges.• Independently document methodologies, findings, and results in a clear and concise manner, ensuring reproducibility and knowledge sharing.• Collaborate with cross-functional teams, including applied scientists, software engineers, and product managers, to integrate LLM-based solutions into Amazon's customer service platforms. • Develop and implement strategies for data collection, annotation, and model training to ensure high-quality and robust performance of the chatbots.• Conduct experiments and evaluations to measure the performance of the developed models and systems, and identify areas for improvement. Stay up-to-date with the latest advancements in NLP, LLMs, and conversational AI, and explore opportunities to incorporate new techniques and technologies into Amazon's customer service solutions.A day in the lifeWe thrive on solving challenging problems to innovate for our customers. By pushing the boundaries of technology, we create unparalleled experiences that enable us to rapidly adapt in a dynamic environment. Our decisions are guided by data, and we collaborate with engineering, science, and product teams to foster an innovative learning environmentIf you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!Benefits Summary: Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) PlanAbout the teamJoin our team of scientists and engineers who develop and deploy LLM-based Conversational AI systems to enhance Amazon's customer service experience and effectiveness. We work on innovative solutions that help customers solve their issues and get their questions answered efficiently, and associate-facing products that support our customer service associate workforce.BASIC QUALIFICATIONS- 3+ years of data scientist experience- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience- Experience applying theoretical models in an applied environment- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science ...

The Data Scientist in NLP within Customer Engagement Tech, Self-Service and Automation team will work on the research, design, and implementation of solutions to key challenges in developing, evaluating and deploying solutions based on large pretrained language models into conversational AI systems that can understand and communicate with customers in a natural and contextually appropriate manner. This involves model development in areas such as multi-turn dialogue management, knowledge grounding, and open-ended generation and assessment of dialogue quality and style of the conversational model.Key job responsibilities1. Lead the development of LLM-based chatbots and conversational AI systems for customer service applications.2. Implement state-of-the-art NLP and ML models for tasks such as language understanding, dialogue management, and response generation and dialogue quality assessment.3. Collaborate with cross-functional teams, including applied scientists, software engineers, and product managers, to integrate LLM-based solutions into Amazon's customer service platforms.4. Develop and implement strategies for data collection, annotation, and model training to ensure high-quality and robust performance of the chatbots.5. Conduct experiments and evaluations to measure the performance of the developed models and systems, and identify areas for improvement.6. Stay up-to-date with the latest advancements in NLP, LLMs, and conversational AI, and explore opportunities to incorporate new techniques and technologies into Amazon's customer service solutions.A day in the lifeWe thrive on solving challenging problems to innovate for our customers. By pushing the boundaries of technology, we create unparalleled experiences that enable us to rapidly adapt in a dynamic environment. Our decisions are guided by data, and we collaborate with engineering, science, and product teams to foster an innovative learning environmentIf you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!Benefits Summary: Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) PlanAbout the teamJoin our team of scientists and engineers who develop and deploy LLM-based Conversational AI systems to enhance Amazon's customer service experience and effectiveness. We work on innovative solutions that help customers solve their issues and get their questions answered efficiently, and associate-facing products that support our customer service associate workforce.BASIC QUALIFICATIONS- 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience- 5+ years of data scientist experience- Experience with unstructured textual data- Experience working with scientists, economists, software developers, or product managers- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science- 5+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience- Experience applying theoretical models in an applied environment ...

Amazon Q in Connect (QiC) provides customer service agents with recommendations for what to say and do (including step-by-step guides) to resolve customer issues faster, improving customer satisfaction and reducing costs. QiC reduces agent handle times and will improve resolution rates through its ability to understand complex customer objectives, synthesize relevant information from diverse sources (e.g., customer data, contact transcripts, knowledge articles), and generate human-like responses or take actions personalized to an end-customer’s situation. QiC will generate usage data (e.g., what actions that agents do or do not take on QiC responses) that enables QiC to learn and improve with an “agent in the loop,” increasing QiC’s accuracy and ability to automate more contact types. Key job responsibilitiesWe are looking for an experienced Data Scientist with a strong machine learning background to lead the development of frameworks that deepen understanding of agent assistance and improve automation in Call Center environments.Bringing to bear a mixture of model development and software engineering skills, you will lead the development and deployment and of several of Q in Connect's core assistant models, use data-driven methods to answer business questions, and deliver insights to deepen understanding of Amazon Connect agents and end-customers.About the teamWhy AWSAmazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.Inclusive Team CultureHere at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.Work/Life BalanceWe value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.Mentorship and Career GrowthWe’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.Diverse ExperiencesAmazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.BASIC QUALIFICATIONS- 2+ years of data scientist experience- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience- Experience applying theoretical models in an applied environment ...

Amazon Music is an immersive audio entertainment service that deepens connections between fans, artists, and creators. From personalized music playlists to exclusive podcasts, concert livestreams to artist merch, Amazon Music is innovating at some of the most exciting intersections of music and culture. We offer experiences that serve all listeners with our different tiers of service: Prime members get access to all the music in shuffle mode, and top ad-free podcasts, included with their membership; customers can upgrade to Amazon Music Unlimited for unlimited, on-demand access to 100 million songs, including millions in HD, Ultra HD, and spatial audio; and anyone can listen for free by downloading the Amazon Music app or via Alexa-enabled devices. Join us for the opportunity to influence how Amazon Music engages fans, artists, and creators on a global scale. Learn more at https://www.amazon.com/music.We are seeking a highly skilled and analytical Data Scientist. You will play an integral part in the Finance and marketing workstreams. You will have the opportunity to work with rich datasets together with the marketing and finance managers. This role will focus on developing and implementing causal and econometric models for financials and marketing effectiveness and inform strategic decision-making as well as financial planning. This role is suitable for candidates with strong background in causal inference, statistical analysis, and data-driven problem-solving, with the ability to translate complex data into actionable insights. Key job responsibilitiesDevelop Causal ModelsDesign, build, and validate causal models to evaluate the impact of marketing campaigns and initiatives. Leverage advanced statistical methods to identify and quantify causal relationships. Build forecasting models to predict business outcomesConduct Randomized Controlled TrialsDesign and implement randomized controlled trials (RCTs) to rigorously test the effectiveness of marketing strategies. Ensure robust experimental design and proper execution to derive credible insights.Statistical Analysis and InferencePerform complex statistical analyses to interpret data from experiments and observational studies. Use statistical software and programming languages to analyze large datasets and extract meaningful patterns.Data-Driven Decision MakingCollaborate with finance and marketing teams to provide data-driven recommendations. Present findings and insights to stakeholders in a clear and actionable manner.Collaborative Problem SolvingWork closely with cross-functional teams, including marketing, finance, product, and engineering, to identify key business questions and develop analytical solutions. Foster a culture of data-informed decision-making across the organization.Stay Current with Industry TrendsKeep abreast of the latest developments in data science, causal inference, forecasting and marketing analytics. Apply new methodologies and technologies to improve the accuracy and efficiency of marketing measurement.Documentation and ReportingMaintain comprehensive documentation of models, experiments, and analytical processes. Prepare reports and presentations that effectively communicate complex analyses to non-technical audiences.BASIC QUALIFICATIONS- 1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience- 2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience ...

Are you a passionate Data Scientist (DS) ready to shape the future of digital content creation? At Amazon, we're building Earth's most desired destination for creators to monetize their unique skills, inspire the next generation of customers, and help brands expand their reach. We build innovative products and experiences that drive growth for creators across Amazon's ecosystem. Our team owns the entire Creator product suite, ensuring a cohesive experience, optimizing compensation structures, and launching features that help creators achieve both monetary and non-monetary goals.Key job responsibilitiesAs a DS in our team you will:* Collaborate with cross-functional leaders from business development, marketing, product, and engineering to implement measurable, data-driven strategies * Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and implementation.* Perform large-scale experimentation to identify hidden relationships between variables in large datasets* Implement statistical, machine learning, or other mathematical methodologies to solve specific business problems* Coordinate research and analysis activities using unstructured and structured data and use programming to clean and organize data* Foster a culture of continuous learning and innovationThe successful candidate is self-driven and thrives in a fast-paced, innovative environment. You have deep expertise in accessing, manipulating, analyzing, and modeling large datasets across various platforms. You possess strong business acumen and excellent communication skills, and use them to effectively translate business requirements into scientific solutions. You stay current with emerging technologies and implement them strategically. About the teamOur team is dedicated to supporting new members. We have a broad mix of domain specialists (Economics, Data Science, Applied Science), experience levels and tenures, and we’re building an environment that celebrates knowledge creation and 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.BASIC QUALIFICATIONS- Master's degree or above in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science- 2+ years of machine learning, statistical modeling, data mining, and analytics techniques experience- 2+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience- Experience in communicating technically, at a level appropriate for the audience- 2+ years of data scientist experience ...