Data Science

At Amazon Web Services (AWS), we’re hiring highly technical Data Analytics consultants to collaborate with our customers and partners on key engagements. Our consultants will develop and deliver proof-of-concept projects, technical workshops, and support implementation projects. These professional services engagements will focus on customer solutions such as Data and Analytics, Artificial Intelligence (AI) and GenerativeAI (GenAI), Machine Learning (ML), HPC and more.You will join as part of the AWS Professional Services (ProServe) Associate to Consultant (A2C), which focuses on the accelerate career development of university graduates and early career professionals. Our team members work with enterprise customers locally, regionally and domestically. As such, this role has up to 75% travel associated. While many of our customers engage ProServe virtually, there is always the potential that a customer might choose to include travel in their contract.Key job responsibilitiesIn this role, you will work with our partners, customers and focus on our AWS offerings such Amazon Kinesis, AWS Glue, Amazon Redshift, Amazon EMR, Amazon Athena, Amazon SageMaker, Amazon Bedrock, Amazon Q, and Amazon Lex. You will help our customers and partners to remove the constraints that prevent them from leveraging their data to develop business insights. The ideal candidate will have extensive experience with design, development and operations that leverages deep knowledge in the use of modern data services like DynamoDB, Amazon Kinesis, Apache Kafka, Apache Spark, Amazon Sagemaker, Amazon RDS, technologies and other industry data structures and standards.A day in the lifeAWS Professional Services engage in a wide variety of projects for customers and partners, providing collective experience from across the AWS customer base and are obsessed about customer success. Our team collaborates across the entire AWS organization to bring access to product and service teams, to get the right solution delivered and drive feature innovation based upon customer needs.You will also have the opportunity to create white papers, writing blogs, build demos and other reusable collateral that can be used by our customers. Most importantly, you will work closely with our Solution Architects, Data Scientists and Service Engineering teams.About the teamInclusive Team CultureHere 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 BalanceOur 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 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. 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* Bachelor’s degree or higher in Computer Science, Engineering, Mathematics or a related field with a conferral date within May 2023 to May 2025* 1+ years of hands-on experience of programming in languages such as Python, Ruby, Go, Swift, Java, .Net, C++, Node.js, or similar object-oriented language. ...

Advertising Amazon Marketing Cloud (AMC) teams build Advanced Analytics System that are secure, privacy-safe, and dedicated cloud-based environment in which advertisers can easily perform analytics across multiple, pseudonymized data sets to generate aggregated reports. Inputs can include an advertiser’s own data sets, as well as their Amazon Advertising campaign events, such as impressions, clicks, and conversions. The services you will work on are directly used by our customers and operate at Big Data scale, ingesting and processing billions of behavioral signals every day. Speed, scale, and accuracy are critical to our success. The successful candidate will be a self-starter, comfortable with ambiguity and be able to create and maintain efficient, automated, end-to-end data solutions and services. They know and love working with data engineering tools, can model multidimensional datasets, and can partner effectively with business leaders to build the right data solutions to answer key business questions. They will build efficient, flexible, extensible, and scalable data models, ETL designs and data integration services. They will also be required to support and manage growth of these data solutions. They are analytical and creative, and don’t quit. This is a role with high visibility to senior leadership and with high opportunity for impact for those willing to roll up their sleeves and dive deep to achieve results.If I were hired, what would I be working on?In this role, you will build and maintain customer facing data products and data solutions for our Amazon Advertising customers using engineering best practices, data management fundamentals, data storage principles, and operational excellence best practices. You will work closely with other engineering and product teams across Amazon Advertising to provide the high quality and scalable big data flow for datasets. This is a large initiative that spans across multiple existing and to be formed engineering and product teams within the Advertising organization. Why should I join your team? Are you interested in building a green field product opportunity within Amazon Advertising? Do you want to have direct and immediate impact on millions of customers every day? If you are a self-starter, enjoy designing large scale distributed and orchestration systems, and are intrigued by ambiguous problems, this is a unique and rare opportunity to build a new initiative from scratch with some of the best full-stack engineers at Amazon. We pioneer the usage of modern full-stack technologies at Amazon scale!We’re looking for experienced, motivated Data Engineer with a proven track record of leading large scale initiatives that span across multiple organizations. If you are passionate about developing analytical solutions to solve business problems, and you are looking for a team that drives results that influence Amazon’s business, this is the right place for you.About the teamAmazon Marketing Cloud (AMC) is an advanced analytics product that is secure, privacy-safe, and dedicated cloud-based environment in which advertisers can easily perform analytics across multiple, pseudonymized data sets to take actions for their Advertising Activities. AMC unlocks advanced campaign measurement, audience refinement, supply optimization, and more, enabling advertisers to make more informed decisions about their cross-channel marketing investments. Our services ingest billions of behavioral signals every day. Speed, scale, and accuracy are critical to our success.AMC: https://advertising.amazon.com/solutions/products/amazon-marketing-cloudKey job responsibilities- Develop data products, infrastructure, and Big Data solutions and services leveraging Native AWS services (such as Redshift, Kinesis, EMR, Lambda etc.)- Develop new data models and end to data pipelines.- Collaborate with a team of other Data Engineers and Software Development Engineers on data delivery best practices.- Contribute to infrastructure planning and operational excellence continued improvements.- Lead and participate in engineering design reviews for solutionsAbout the teamOur 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. 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 help each team member 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 ...

Join Amazon's Global Logistics team as a Data Scientist and drive operational excellence through advanced analytics. You'll leverage your passion for optimizing business processes and performance metrics to identify high-impact opportunities. In this role, you'll design and implement scalable solutions, dive deep into complex data, and communicate insights that shape the future of our global logistics network.Key job responsibilities- Design and implement data-driven approaches to support decision-making across the business- Apply a range of scientific techniques to solve complex business problems with unclear solutions- Develop and automate large-scale analyses using cutting-edge algorithms and tools- Validate findings against alternative approaches and key performance indicators- Build strong relationships with stakeholders to drive improvements and prioritize customer needsA day in the lifeAs a Data Scientist in Global Logistics, you'll start your day by reviewing the latest data trends and system performance metrics. You might collaborate with cross-functional teams to understand operational challenges, then dive into data analysis using advanced statistical methods. You'll develop models to optimize logistics processes, present findings to business partners, and work on implementing solutions that directly impact Amazon's global supply chain efficiency.About the teamOur Global Logistics Data Science team is dedicated to revolutionizing the way Amazon moves products around the world. We're passionate about leveraging data to create innovative solutions that enhance customer experience, reduce costs, and improve sustainability. Join us in shaping the future of logistics through cutting-edge analytics and machine learning applications.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) Plan Learn more about our benefits here: https://www.amazon.jobs/en/internal/benefits/us-benefits-and-stockBASIC 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 ...

Amazon Web Services (AWS) is the world leader in providing a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers hundreds of thousands of businesses in 190 countries around the world! Passionate about building, owning and operating massively scalable systems? Want to make a billion-dollar impact? If so, we have an exciting opportunity for you. The AWS Managed Operations (MO) organization was founded in April 2023, with the objective to reduce operational load and toil through long-term engineering projects. MO is building the best-in-class engineering and operations team that will own the day-to-day operations for AWS Regions; improving the availability, reliability, latency, performance and efficiency to operate AWS regions. The AWS Managed Operations Data Science (MODS) Team is looking for a Data Scientist to lead the research and thought leadership to drive our data and insight strategy for AWS. You will be expected to serve as a Full Stack Data Scientist. You will be responsible for driving data-driven transformation across the organization. In this role, you will be responsible for the end-to-end data science lifecycle, from data exploration and feature engineering and ETL to model development. You will leverage a diverse set of tools and technologies, including SQL, Python, Spark, Hugging Face and various machine learning frameworks, to tackle complex business problems and uncover valuable insights.Your product analytics research will provide direction on the technology strategy of the Managed Operations organization. Your Decision Science artifacts will provide insights that inform AWS' Operations and Site Reliability Engineering teams. You will work on ambiguous and complex business and research science problems at scale. You are and comfortable working with cross-functional teams and systems.This position requires that the candidate selected be a U.S. citizen.10012Key job responsibilities- Collaboration & Cross Functional Relationships: Interact with business and software teams to understand their business requirements and operational processes- Data Exploration and Analysis: Conduct in-depth exploratory data analysis to understand the structure, quality, and patterns within complex datasets. Apply statistical and machine learning techniques to extract insights, identify trends, and uncover hidden relationships in the data. - Business Insights and Recommendations: Frame business problems into scalable solutions; translate complex data insights and model outputs into actionable recommendations that address the organization's strategic objectives.- Data Pipeline and Infrastructure: Contribute to the design and implementation of data pipelines, data lakes, and other data infrastructure components to support the organization's data-driven initiatives.- Metric Development and Monitoring: Define and develop advanced, customized metrics and key performance indicators (KPIs) that capture the nuances of the organization's strategic objectives and operational complexities. Continuously monitor and evaluate the performance of metrics - Prototype models by using high-level modeling languages such as R or in software languages such as Python. A software team will be working with you to transform prototypes into production.- Documentation & Continuous Improvement: Create, enhance, and maintain technical documentationA day in the lifeWhy 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.Utility 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 their cloud services.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.About the teamThe MODS team is driven by a shared vision of achieving operational excellence through data analytics and machine learning. We provide actionable insights to allow our stakeholders to manage operational posture and operator experience and drive sustainable, safe, and efficient operations. We define, monitor, and predict metrics to provide recommendations on AWS operations that are diagnostic (why something happened), predictive (what will happen) and prescriptive (best course of action) in nature. We are a customer obsessed team driving lean operations in all of AWS through actionable insights and data strategies that drive process improvement. This position requires that the candidate selected be a U.S. citizen.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- Knowledge of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.- Master's Degree in Statistics, Applied Math, Operations Research, Economics, or a related quantitative field with 2+ years' experience in Data Science or related Science discipline, OR, Bachelor's Degree in Statistics, Applied Math, Operations Research, Economics, or a related quantitative field with 5+ years' experience in Data Science or related Science discipline ...

Amazon Prime’s Science organization leads the Research & Development towards innovation for Amazon Prime. Amazon Prime is the backbone of Amazon’s consumer business and aspires to be the world’s most engaging, satisfying, and loved membership program, driving growth and profitability. The program serves over 200 million members across 25 countries and is key to Amazon’s customer growth and engagement. Prime Science innovates in Artificial Intelligence and Economics, to develop algorithms and systems for automated marketing, personalization, targeting, and decisioning. To lead Prime’s growth and impact through science and innovation, we are seeking a Principal Applied Scientist, Prime Science, to create and deliver Machine Learning innovation both for customer facing and internal solutions. To be successful in this role you should be recognized as an industry expert who has experience defining a long-term science vision, driven fundamentally from the needs of customers, translating that direction into specific plans for research scientists, applied scientists, engineering, and product teams. This is a role that combines science leadership, organizational ability, technical expertise, product focus, and business understanding.Prime is committed to diversity, equity, and inclusion and recognizes that our ability to serve our members is contingent on having diverse backgrounds, ideas, and ways of working on our team. This leader plays a key role as a member of the Prime worldwide leadership team to set the right organizational vision, standards, and mechanisms to ensure Prime is the best place for top talent to thrive. Key job responsibilities- Own and drive the most complex and strategic solutions across the business; responsible for many billions in revenue.- Act as a thought leader and forward thinker, anticipating obstacles to success and helping avoid common failure modes.- Research, build, and deploy innovative machine learning solutions; working across all technical disciplines.- Partner with science, engineering, and product leaders across the business to identify and deliver innovative machine solutions; identify new opportunities, define the vision and execute solutions that continually delight customers.- Hire, mentor, and guide senior scientists; partner with engineering leaders to build efficient and scalable solutions.BASIC QUALIFICATIONS- Ph.D. in Machine Learning, Computer Science, or related disciplines.- 10+ years of post-Ph.D. experience, delivering highly effect machine learning solutions that solve real-world problems at a very large scale.- Expert in machine learning, statistics, and experiment design.- Expert in taking machine learning solutions into production at a large scale.- Experience with Large Language Models and Generative AI.- Experience hiring and building teams of applied scientists.- Proven communication and collaboration skills that enable you to earn trust at all levels of a large organization; ability to influence ...

The Seller Insights and Planning team’s mission is to make FBA the best place for sellers to both thrive and delight customers. We achieve this through identifying opportunities to address seller pain points, optimizing our services to reduce seller effort, eliminating the defects that lead to seller costs, and orchestrating initiatives across business, technology and operations that simplify the seller experience.As a Data Engineer in this role, you’ll have an opportunity to design, develop, and maintain a data lake that supports engineering, product, and business teams internationally within the Worldwide FBA business. Achieving this will require developing scalable data pipelines and systems that enable efficient and reliable data processing and integration from multiple sources owned by teams distributed internationally. Collaborating closely with cross-functional teams, you will need to determine engineering requirements and implement solutions that support our business intelligence and analytics initiatives, particularly focused on Worldwide FBA performance. The ideal candidate will be technically proficient (at the Data Engineering Coding bar), possess a strong background in data engineering, and have a deep understanding of data architecture. Key job responsibilitiesDesign, build, and maintain scalable and robust data pipelines for extracting, transforming, and loading (ETL) data from various structured and unstructured sources.Develop solutions to integrate data from multiple internal and external sources, ensuring accuracy, consistency, and reliability. Manage data storage solutions to optimize performance and cost-efficiencyDesign and implement efficient data models and schemas for business intelligence, analytics, and reporting. Ensure these models are optimized for performance, scalability, and accessibilityCollaborate with data analysts, BI engineers, software developers, and other stakeholders to understand data needs and provide solutions aligned with business requirements. Engage in cross-functional projects to support WW FBA initiativesImplement and maintain data validation processes to ensure high data quality and integrity. Establish data governance frameworks to enforce data security, privacy, and compliance standardsMaintain comprehensive documentation of data architecture, pipeline designs, and data models. Promote and enforce best practices for data engineering within the teamBASIC QUALIFICATIONS- Bachelor's degree in quantitative study such as Computer Science, Computer Engineering, Mathematics, or equivalent experience- 3+ years of data engineering experience- 3+ years of writing advanced SQL queries- Experience with data modeling, warehousing, and building ETL pipelines- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, R, or NodeJS- Proficiency in written and verbal communication skills including comfortability communicating and presenting to senior leadership ...

Prime Video offers customers a vast collection of movies, series, and sports—all available to watch on hundreds of compatible devices. U.S. Prime members can also subscribe to 100+ channels including Max, discovery+, Paramount+ with SHOWTIME, BET+, MGM+, ViX+, PBS KIDS, NBA League Pass, MLB.TV, and STARZ with no extra apps to download, and no cable required. Prime Video Personalization and Discovery team is building a new Data Platform . The platform will streamline ML and engineering teams to access and leverage high-quality, consistent customer-level data for offline processing and in real-time adhering to committed SLAs. We will act as guardians and gatekeepers of data shielding our customers from data issues while collaborating with data sources to address problems at their root. We will own and maintain "golden" datasets — centralized, reliable data assets commonly used across teams to train ML models and deliver top-notch personalized storefront experience, that is unique for every PV end-customer. We will own Data Registry; we ensure that datasets are enriched with comprehensive classification and metadata, making them easily discoverable and accessible, and enabling ML and engineering teams to focus on deriving value for end customers rather than resolving data inconsistencies. Our goal is to save time for science and engineering teams to work with customer-level data, avoid duplicated boiler-plate data transformations, quality inspections, save IMR costs and increase experimentation velocity. Key job responsibilities- Design and build big data pipelines via Spark/Flink that can handle Petabytes of data per month- Build resilient data pipelines with extensive unit tests/integration tests with CI/CD development lifecycle- Participate in oncall rotation supporting a large number of production data pipelines- Manage and orchestrate version migrations across the metadata, transform, and storage layers.- 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. - Work closely with Product teams, Data Scientists, 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.)About the teamOur vision is to build a resilient, centralized data platform that distributes and streamlines access to the high quality, easily-discoverable customer-level data for offline processing and in real-time, enabling PVPD science and engineering teams to accelerate the focus on ML and engineering innovations to enhance personalization of PV end customer experiences. BASIC QUALIFICATIONS- 3+ years of data engineering experience- Experience with data modeling, warehousing and building ETL pipelines- Experience with SQL ...

Amazon Web Services (AWS) is a dynamic and rapidly growing business within Amazon and the leader in providing secure, reliable, scalable, and innovative services that help over a million businesses, governments, education, and not for profits across the globe scale and grow! AWS provides a wide set of scalable services to meet customer needs.The AWS Global Deal Strategy and Programs (GDSP) organization is responsible for the Private Pricing Program. The Private Pricing Analytics and Insights (PPA&I) team owns building scalable analytical solutions that enable the GDSP organization with actionable insights to make data-driven decisions. This role will focus on Data Engineering, and Analytics related to the Private Pricing Program, requiring deep technical skills, strong business acumen and a deep analytical background to provide actionable data-driven insights and decision support.As a Senior Data Engineer on this team, you will drive efficiency in data handling processes, setup product analytics, drive advanced analysis and build new metrics which are key inputs to improve the health, scale and growth of the Private Pricing Program. You will work collaboratively with the business leaders (including the VP of Private Pricing), operations, and engineering teams on many non-standard and unique business problems and support business initiatives by collecting required and related data from external/internal sources.The ideal candidate should have strong communication skills and ability to prioritize effectively to ensure timelines are met. You will own projects E2E, from engaging with customers to production and delivery of a suite of tools used by the organization to make key business decisions. You should be a self-starter, comfortable with ambiguity, able to think big and be creative (while still paying careful attention to detail). You think in terms of architecture, not just code. You proactively work to improve the consistency and integration between your team’s BI solutions and any related systems or artifacts.Key job responsibilities Owning the design, development, and maintenance of scalable solutions for ongoing metrics, reports, analyses, dashboards, etc. to support analytical and business needs• Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using AWS services and internal tools• Build and deliver high quality data sets to support data scientists and customer reporting needs.• Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers• Translate basic business problem statements into analysis requirements.• Use analytical and statistical rigor to answer business questions and drive business decisions.• Find and create ways to measure the customer experience to drive business outcomes.• Develop queries and visualizations for ad-hoc requests and projects, as well as ongoing reporting.• Write queries and output efficiently, and have in-depth knowledge of the available in area of expertise. Pull the needed with standard query syntax; periodically identify more advanced methods of query optimization. Convert to make it analysis-ready.• Recognize and adopt best practices in reporting and analysis: integrity, design, analysis, validation, and documentation.• Troubleshoot operational quality issues.• Review and audit existing jobs and queries.• Recommending improvements to back-end sources for increased accuracy and simplicity.About the teamDiverse Experiences:AWS 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. Why AWS?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.Inclusive Team Culture: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.Mentorship & Career Growth: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. Work/Life Balance:We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. 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 ...

Are you interested in helping build a world-class transportation network for Amazon as we delight our customers with more 1 day promises and also meet our sustainability targets ? Do you want to deliver products at scale influence the network design of one of the most complex transportation network in the world? Amazon Worldwide Operations is looking for a Data Scientist. The role will require modeling, auditing and optimizing our transportation network from our fulfillment centers to our last mile carriers who deliver packages to customers.To be successful in the role, you need strong analytical skills, excellent communication skills, ability to influence across business functions and manage stakeholders’ expectations effectively. You will work in a fast-paced environment that requires you to be detail-oriented and comfortable in working with multiple business and technical teams.This position has the option to be located in Bellevue WA, Austin TX, Nashville TN, Santa Monica CA, Arlington VA, New York City NY, or Toronto CA. Key job responsibilities- Development of scalable data science solutions to audit and optimize our transportation network.- Development and execution of analytical tools to model our transportation network.- Contribute to the strategy for network design, prioritize technical and operational initiatives, evaluate and set stakeholders expectations.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 ...

The Selling Partner Experience (SPX) organization strives to make Amazon the best place for Selling Partners to do business. The SPX Science team is building an AI-powered conversational assistant to transform the Selling Partner experience. The Selling Assistant is a trusted partner and a seasoned advisor that’s always available to enable our partners to thrive in Amazon’s stores. It takes away the cognitive load of selling on Amazon by providing a single interface to handle a diverse set of selling needs. The assistant always stays by the seller's side, talks to them in their language, enables them to capitalize on opportunities, and helps them accomplish their business goals with ease. It is powered by the cutting edge of Generative AI, going beyond a typical chatbot to provide a powerful, personalized experience to sellers running real businesses, large and small.Do you want to join an innovative team of scientists, engineers, product and program managers who use state-of-the-art Generative AI and Machine Learning technologies to help Amazon create a delightful Selling Partner experience? Do you want to build solutions to real business problems by automatically understanding and addressing sellers’ challenges, needs and opportunities? Are you excited by the prospect of contributing to one of Amazon’s most strategic Generative AI initiatives? If yes, then you may be a great fit to join the Selling Partner Experience Science team (SPeXSci).Key job responsibilities- Manage scientists who use state-of-the-art Machine Learning and Generative AI techniques to create the next generation of the tools that empower Amazon's Selling Partners to succeed.- Drive design, development and deployment of highly innovative models to interact with Sellers and delight them with solutions.- Work closely with teams of scientists and software engineers to drive real-time model implementations and deliver novel and highly impactful features.- Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.- Oversee research and implementation of novel machine learning and statistical approaches.- Participate in strategic initiatives to employ the most recent advances in ML in a fast-paced, experimental environment.About the teamSelling Partner Experience Science (SPeXSci) is a growing team of scientists, engineers and product leaders engaged in the research and development of the next generation of ML-driven technology to empower Amazon's Selling Partners to succeed. We draw from many science domains, from Natural Language Processing to Computer Vision to Optimization to Economics, to create solutions that seamlessly and automatically engage with Sellers, solve their problems, and help them grow. We are focused on building seller facing AI-powered tools using the latest science advancements to empower sellers to drive the growth of their business. We strive to radically simplify the seller experience, lowering the cognitive burden of selling on Amazon by making it easy to accomplish critical tasks such as launching new products, understanding and complying with Amazon’s policies and taking actions to grow their business.BASIC QUALIFICATIONS- 3+ years of scientists or machine learning engineers management experience- Knowledge of ML, NLP, Information Retrieval and Analytics- Experience directly managing scientists or machine learning engineers ...

Project Kuiper is an initiative to launch a constellation of Low Earth Orbit satellites that will provide low-latency, high-speed broadband network connectivity to unserved and underserved communities around the world.Key job responsibilitiesThe Kuiper SMART team is a team of Machine Learning Engineers, Scientists, and Data Engineers that is working with stakeholders across Kuiper to solve ML and AI problems. We are looking for a passionate, talented, and inventive Applied Scientist with a background in AI, Gen AI, Machine Learning, NLP, to lead delivering best in class automated customer service and business analytic solutions for our partner, the Kuiper Customer Service team. As an Applied Scientist, you will be responsible for the development, fine-tuning, and evaluation of AI models that power our chatbot and IVR solutions. Your work will ensure the chatbot and IVR is accurate, reliable, and continually improving to meet customer needs. This role involves collaborating with cross-functional teams to integrate AI solutions into our customer service platform, monitor their performance, and implement ongoing enhancements.The ideal candidate has experience in successfully building chat bots using AI technologies, measuring their performance and delivering ongoing improvements.About the teamIn Project Kuiper, we believe that our differences makes us stronger. We are committed to Amazon’s culture of inclusion ingrained in our Leadership Principles, which encourages team members to seek diverse perspectives, learn and be curious, and earn trust. We want to foster a culture of collaboration, delivering results and work/life balance.BASIC QUALIFICATIONS- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

The Bedrock AI Data Team in Amazon Web Services (AWS) is looking for a Language Engineer to collaborate in developing solutions for natural language data collections. This position is an opportunity to apply your expertise in a challenging but supportive environment.The mission of the Bedrock AI Data Team is to engineer the datasets critical to the success of AWS’s Bedrock services. From human evaluations to Responsible AI safeguards to Retrieval-Augmented Generation and beyond, these products make Generative AI enterprise-ready and safe for users, impacting millions of people every day. We are a group of language engineers, linguists, data scientists, data engineers, and program managers, and we partner closely with the science, engineering, and product teams. We are customer obsessed and committed to delivering results with the highest quality and integrity.As a Language Engineer, you will start by diving deep into a couple of critical projects for Bedrock services to drive these projects forward. You will collaborate with fellow language data scientists, program managers, as well as stakeholders in science, engineering, and product teams to understand the role data plays in developing models that meet customer needs. You will analyze, follow, and improve processes for collecting and annotating LLM inputs and outputs, assessing data quality, and automating where appropriate.You will then expand your scope by using the principles of data-centric AI to understand the role our data plays with regard to model performance specifically, as well as the larger ML pipeline. You will apply state-of-the-art Generative AI techniques to analyze how well our data represents human language and run experiments to gauge downstream interactions. You will work collaboratively with other language data scientists and scientists to design and implement principled strategies for data optimization.Key job responsibilities- Source, validate, and deliver high-quality language artifacts and linguistic data- Collaborate with stakeholders to design data collection and development efforts- Oversee the progress and quality of several data collection and annotation projects at a time- Advocate for strict adherence to data collection guidelines and quality thresholds- Extend existing data collection, annotation, and quality assurance efforts to support feature and language expansion- Innovate on data collection methodologies, guidelines, quality metrics to support new requests- Automate repetitive workflows and improve existing processesAbout the teamThe Bedrock AI Data Team at AWS is responsible for delivering high-quality annotated data and a variety of language artifacts to ensure the best performance of different AWS LLM services. These Generative AI services enable customers to readily add intelligence to their business operations and AI applications to drive positive outcomes.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 their cloud services.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. Why AWS?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.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 & 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. 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. Hybrid WorkWe value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.BASIC QUALIFICATIONSMaster’s degree in Linguistics, Computational Linguistics, or other language or data-related disciplines2+ years experience with human data collection studiesProficiency in PythonExperience with language data analysisExperience with command-line environments (e.g. Unix) and version control (e.g. Git)Experience in developing and evaluating data annotation metrics ...

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!As the Data Science Manager on this team, you will: - Lead of team of scientists, business intelligence engineers, etc., on solving science problems with a high degree of complexity and ambiguity.- Develop science roadmaps, run annual planning, and foster cross-team collaboration to execute complex projects.- Perform hands-on data analysis, build machine-learning models, run regular A/B tests, and communicate the impact to senior management.- Hire and develop top talent, provide technical and career development guidance to scientists and engineers in the organization.- Analyze historical data to identify trends and support optimal decision making.- Apply statistical and machine learning knowledge to specific business problems and data.- Formalize assumptions about how our systems should work, create statistical definitions of outliers, and develop methods to systematically identify outliers. Work out why such examples are outliers and define if any actions needed.- Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes.- Build decision-making models and propose effective solutions for the business problems you define.- Conduct written and verbal presentations to share insights to audiences of varying levels of technical sophistication.Why you will love this opportunity: Amazon has invested heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate.Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding.Team video ~ https://youtu.be/zD_6Lzw8raEBASIC QUALIFICATIONS- 5+ years of building quantitative solutions as a scientist or science manager experience- 2+ years of scientists or machine learning engineers management experience- 5+ years of applying statistical models for large-scale application and building automated analytical systems experience- PhD in computer science, mathematics, statistics, machine learning or equivalent quantitative field- Knowledge of Python or R or other scripting language ...

The AWS Kumo team provides technology and trusted expertise that intelligently anticipate and resolve AWS customer needs, helping them adopt, optimize, and operate at scale. Kumo’s products, used by AWS customers and the Support teams that help them, are vital to ensuring exceptional customer experiences on AWS. Our team owns customer facing applications like Trusted Advisor, Personal Health Dashboard, AWS Forums, and Support Center and internal tooling such as Case Management, Troubleshooting, and Customer Event Management. We are a highly innovative global organization revolutionizing the way customers engage and seek help from AWS. Support provides a strategic advantage for customers adopting AWS and drives direct revenue to the business.Key job responsibilitiesWe are looking for an excellent Data Engineer who is passionate about data and the insights that large amounts of data sets can provide. You should possess both a data engineering background and a business acumen that enables you to think strategically. You will experience a wide range of problem solving situations requiring extensive use of data collection and analysis. The successful candidate will work in lock-step with BI Engineers, Data scientists, ML scientists, Business analysts, Product Managers and other stakeholders across organization. A day in the lifeYou will:Develop and improve the current data architecture, data quality, monitoring and data availability.Collaborate with Data Scientists to implement advanced analytics algorithms that exploit our rich data sets for statistical analysis, prediction, clustering and machine learningPartner with BAs across teams to build and verify hypothesis to improve the AWS Support business.Help continually improve ongoing reporting and analysis processes, simplifying self-service support for customersKeep up to date with advances in big data technologies and run pilots to design the data architecture to scale with the increased data sets of customer experience on AWS.About the teamDiverse 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.Why 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.Work/Life BalanceWe value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our 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.AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.BASIC QUALIFICATIONS- 3+ years of data engineering experience- Experience with data modeling, warehousing and building ETL pipelines ...

Are you passionate about using Data as a way to enable automation, knowledge extraction, and artificial intelligence through the use of Machine Learning, Natural Language Processing, Recommender systems, Computer Vision, and Optimization? We are building a team of experienced Engineers to support this vision.On this team you will partner with a mature team of Software Engineers and Scientists to create the infrastructure and processes needed to support ML models and analyze/model customer reading behavior to measure engagement and detect risks, study and optimize manufacturing and fulfillment processes, and build AI-based systems.Our team has green-field opportunities to create the right data infrastructure to support these use cases. We offer autonomy, value end-to-end, ownership, and a strong partnership with our experienced sister teams.As a Sr Data Engineer, you will help define, design, implement and test the data process and infrastructure to productionalize and monitor ML models for multiple use cases.As a Sr Data Engineer, you will be working with a large and complex dataset. You should have deep expertise in the design, creation, management, and business use of extremely large datasets. You should be expert at designing, implementing, and maintaining stable, scalable, low cost data infrastructure.The successful candidate will be an expert with SQL, ETL (and general data wrangling) and have exemplary communication skills. The candidate will need to be a self-starter, comfortable with ambiguity in a fast-paced and ever-changing environment, and able to think big while paying careful attention to detail.Come join us as we continue to revolutionize the book industry!Key job responsibilities Deliver large data solutions in difficult or ambiguous data areas (new or existing systems). Create data solutions that are easily usable by customers – inventive, secure, maintainable, scalable, and extensible. Build data solutions that are easy for others to contribute to. Know how to make data auditable, available, and accessible. Provide significant knowledge/experience with data design approaches and industry technologies. Evaluate end-to-end data designs for strengths and weaknesses (data quality, scalability, latency, security, performance, data integrity, etc.). Anticipate data access patterns and remove bottlenecks. Ask the right questions and drive the right technical solution(s). Split development work into parallel tasks that can be performed by them and others and reassembled successfully. Influence team technical strategy. Understand that not all problems are new (or require new data solutions). Make appropriate architectural trade-offs. Show good judgment when making technical trade-offs between short-term technology needs and long-term business needs Take ownership of team’s data architecture and make it simpler. Proactively fix an architecture deficiency. Resolve root cause. Drive data engineering best practices and set standards. Understand system limitations, scaling factors, boundary conditions, and/or the reasons for architectural decisions.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 ...

Excited by Big Data, Machine Learning, and Predictive Software? Interested in creating new state-of-the-art solutions using Machine Learning and Data Mining techniques on Terabytes of Data?At Amazon Global Logistics (AGL), our vision is to become the carrier of choice for all of our Selling Partners' cross-border shipping needs, offering a complete set of end-to-end cross-border solutions from key manufacturing hubs to footprint countries, supporting businesses that use Amazon to grow their business globallKey job responsibilities- Utilize machine learning, data mining, and statistical techniques to create new, scalable solutions for business problems.- Analyze and extract relevant information from business data to help automate and optimize key processes.- Design, develop, and evaluate highly innovative models for predictive learning.- Establish scalable, efficient, automated processes for large-scale data analyses, model development, model validation, and model implementation.- Research and implement novel machine learning and statistical approaches.A day in the lifeAs a Data Scientist III in the Business Insight team at Amazon Global Logistics, you will be responsible for developing state-of-the-art large-scale Machine Learning Services involving vast amounts of data and macroeconomic inputs. Your primary focus will be to produce robust forecasts to aid operational excellence and continue improving the customer experience.You will collaborate with cross-functional teams to understand seller behaviors and their impacts on demand generation, demand forecasting, pricing strategies, and asset utilization, especially in areas with variable demand. Your expertise in machine learning, data mining, and statistical techniques will be crucial in creating scalable solutions that drive business impact.About the teamThe Business Insight team at Amazon Global Logistics is dedicated to leveraging data and advanced analytics to drive operational excellence and enhance the customer experience. As we expand our global logistics operations, the need for solid understanding of seller behaviors, demand forecasting, pricing strategies, and asset utilization becomes increasingly vital.Our team comprises talented and experienced professionals who are passionate about applying innovative machine learning techniques to real-world problems and converting them into highly business-impacting solutions. We foster a collaborative environment that encourages creativity, continuous learning, and a strong commitment to delivering exceptional results.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) Plan Learn more about our benefits here: https://www.amazon.jobs/en/internal/benefits/us-benefits-and-stockBASIC QUALIFICATIONS- 4+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience- 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- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or Bachelor's degree and 8+ years of professional or military experience- Experience with statistical models e.g. multinomial logistic regression ...

At Audible, we believe stories have the power to transform lives. It’s why we work with some of the world’s leading creators to produce and share audio storytelling with our millions of global listeners. We are dreamers and inventors who come from a wide range of backgrounds and experiences to empower and inspire each other. Imagine your future with us.ABOUT THIS ROLEIn this role, you'll employ scalable cutting-edge machine learning (ML), deep learning (DL), and Natural Language Processing (NLP) techniques to detect and predict fraudulent activities, enhance fraud investigation capabilities, and develop advanced fraud protection and defense mechanisms. You'll leverage these technologies to analyze complex patterns in transaction data, identify anomalies, and create predictive models that can anticipate potential fraud before it occurs. Your work will be crucial in safeguarding the company's assets, protecting customers from financial harm, and maintaining the integrity of our systems. You'll translate intricate fraud patterns into actionable insights, enabling rapid response to emerging threats and informing critical business decisions related to risk management. You'll operate in an agile environment in which we own and collaborate on the life cycle of research, design, and model development of relevant projects.As an Applied Scientist, you will...- Protect Audible’s customers and content creators against the onslaught of AI-generated fraud- Develop Amazon-scale data engineering & modeling pipelines- Imagine and invent before the business asks, and create groundbreaking fraud detection and mitigation solutions using cutting-edge approaches- Work closely with other data scientists, ML experts, engineers as well as business across the globe, and on cross-disciplinary efforts with other scientists within Amazon- Contribute to the growth of the Audible Data Science team by sharing your ideas, intellectual property and learning from othersABOUT AUDIBLEAudible is the leading producer and provider of audio storytelling. We spark listeners’ imaginations, offering immersive, cinematic experiences full of inspiration and insight to enrich our customers daily lives. We are a global company with an entrepreneurial spirit. We are dreamers and inventors who are passionate about the positive impact Audible can make for our customers and our neighbors. This spirit courses throughout Audible, supporting a culture of creativity and inclusion built on our People Principles and our mission to build more equitable communities in the cities we call home.BASIC QUALIFICATIONS- MS in one of the following disciplines: Computer Science, Statistics, Data Science, Economics, Applied Math, Operational Research or a related quantitative field +5 yrs relevant experience; or PhD- Fluency in Python, SQL or similar scripting languages and skilled at Java, C++, or other programing languages- Experience in algorithm development- Depth and breadth in state-of-the-art machine learning technologies- Machine Learning Pipeline orchestration with AWS (SageMaker, Batch, Lambda, Step Functions) or similar cloud-platforms- Big Data Engineering with Spark / AWS EMR & Glue ...

Have you ever wondered how Amazon launches and maintains a consistent customer experience across hundreds of countries and languages it serves its customers? Are you passionate about data and mathematics, and hope to impact the experience of millions of customers? Are you obsessed with designing simple algorithmic solutions to very challenging problems? If so, we look forward to hearing from you!At Amazon, we strive to be Earth's most customer-centric company, where both internal and external customers can find and discover anything they want in their own language of preference. Our Translations Services (TS) team plays a pivotal role in expanding the reach of our marketplace worldwide and enables thousands of developers and other stakeholders (Product Managers, Program Managers, Linguists) in developing locale specific solutions.Amazon Translations Services (TS) is seeking an Applied Scientist to be based in our Seattle office. As a key member of the Science and Engineering team of TS, this person will be responsible for designing algorithmic solutions based on data and mathematics for translating billions of words annually across 130+ and expanding set of locales. The successful applicant will ensure that there is minimal human touch involved in any language translation and accurate translated text is available to our worldwide customers in a streamlined and optimized manner. With access to vast amounts of data, cutting-edge technology, and a diverse community of talented individuals, you will have the opportunity to make a meaningful impact on the way customers and stakeholders engage with Amazon and our platform worldwide. Together, we will drive innovation, solve complex problems, and shape the future of e-commerce.Key job responsibilities* Apply your knowledge of LLM models to contribute to the development and implementation of machine learning solutions that address language translation-related challenges in the eCommerce space.* Collaborate with cross-functional teams, including senior scientists, software engineers, and product managers, to understand project requirements, map business goals to scientific problems, and help deliver high-quality solutions.* Conduct data analysis to identify patterns and insights, using reasonable assumptions and customer requirements to solve well-defined problems related to seller performance and customer experiences across international marketplaces.* Stay updated on current modeling techniques and methodologies, applying them under guidance to improve the accuracy and efficiency of language translation-related systems.* Communicate technical concepts clearly to team members and stakeholders, participating in discussions on proposed solutions and their potential impact.About the teamWe are a start-up mindset team. As the long-term technical strategy is still taking shape, there is a lot of opportunity for this fresh Science team to innovate by leveraging Gen AI technoligies to build scalable solutions from scratch.Our Vision: Language will not stand in the way of anyone on earth using Amazon products and services.Our Mission: We are the enablers and guardians of translation for Amazon's customers. We do this by offering hands-off-the-wheel service to all Amazon teams, optimizing translation quality and speed at the lowest cost possible.BASIC QUALIFICATIONS- Experience programming in Java, C++, Python or related language- Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse ...

At Amazon, the Leadership Principle “Strive to be Earth’s Best Employer” challenges us to create “a safer, more productive, higher performing, more diverse, and more just work environment,” and reinforces that nothing is more important than the safety and well-being of our teams. At Workplace Health and Safety (WHS) we strive to do just this. We work tirelessly to ensure we have the appropriate strategy, technology, and attitude to be successful. We also understand that people are at the center of safety and look to invest in talent that shares in our passion for making our employees and partners lives better.The WHS Data team is hiring a Business Intelligence Engineer (BIE). The Data team spans the Business Intelligence (BI) and Data Engineering (DE) functional areas, and is responsible with providing all reporting solutions required by the WHS Organization to drive workplace safety and regulatory compliance worldwide. This BIE role will primarily support the data and reporting needs for the Safety Performance Insights (SPI) BI team in the WHS Organization. This role regularly requires close engagement with senior leaders and principal PMs to generate insights and deep dives into core metrics that directly impact organizational strategic decisions and priorities. The role requires high proficiency in complex SQL scripting, often joining together multiple types of data sets that range from normalized summaries to raw information spanning many diverse sources. The role will need to have a high bar for ownership and work autonomously to create high-quality products for the customer. The role is required to communicate project roadmap, prioritization, and release notes of new products with customer and stakeholder groups including leadership.Key job responsibilities-Contribute to the design, implementation, and delivery of BI solutions for complex and ambiguous problems-Conduct deep dive analyses of business problem statements and formulate conclusions and recommendations to leadership-Identify opportunities and key criteria to drive analytical reporting and business strategy-Produce written recommendations and insights for key stakeholders that will help shape effective metric development and reporting-Simplify and automate reporting, audits, and other data-driven activities-Partner with Data Engineering to enhance data infrastructure, data availability, and broad access to customer insights-Develop and drive best practices in data integrity, consistency, analysis, validations, and documentation-Learn new technology and techniques to meaningfully support product and process innovationA day in the lifeAmazon 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) PlanIf 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! BASIC QUALIFICATIONS- Bachelor's degree in BI, finance, engineering, statistics, computer science, mathematics, finance or equivalent quantitative field- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience- Experience with data modeling, warehousing and building ETL pipelines- Experience with data visualization using Tableau, Quicksight, or similar tools ...

We are seeking a talented and experienced Data Engineer II to join our Publisher Ad Server team. In this role, you will be responsible for designing, implementing, and maintaining data pipelines and infrastructure that support our ad serving platform. You'll work closely with cross-functional teams to ensure data accuracy, reliability, and scalability to meet the growing demands of our digital advertising ecosystem.Key Responsibilities:1) Design and develop robust, scalable data pipelines to ingest, process, and analyze large volumes of advertising data from multiple sources.2) Optimize existing data models and create new ones to support ad serving, reporting, and analytics requirements.3) Implement and maintain data quality checks and monitoring systems to ensure data integrity and reliability.4) Collaborate with data scientists, analysts, and product managers to deliver actionable insights and drive data-driven decision making.5) Develop and maintain ETL processes using modern data engineering tools and technologies.6) Optimize query performance and data storage to improve system efficiency and reduce costs.7) Implement data security and privacy measures to ensure compliance with industry regulations (e.g., GDPR, CCPA).8) Contribute to the development of data architecture standards and best practices within the team.9) Troubleshoot and resolve complex data-related issues in a timely manner.10) Stay up-to-date with emerging technologies and industry trends in data engineering and ad tech.About the teamPAS (Publisher Ad Server) builds and operates services that empower 1P publishers to improve monetization, enhance user experience, and reduce infrastructure costs. We bias toward industry standards and flexible designs that allow publishers to invent on top of our solutions and interoperate with other advertising technology providers. Our domain covers core auction functionality and yield optimization across the stages of an ad auction: orchestrating bid requests, selecting ads, and logging events. Our science drives the PAS “smart default” algorithms, including low-latency “decision” algorithms for pacing, podding, dynamic allocation, and auctions during deal/ad selection.BASIC QUALIFICATIONS- 3+ years of data engineering experience- Experience with data modeling, warehousing and building ETL pipelines ...