Data Science

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.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.We are calling on engineers who wants to contribute to a sustainable future through technology. Join us in developing solutions for renewable energy portfolio and reduce carbon footprint of our materials in data centers.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. 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 farmsKey job responsibilitiesOur Business Intelligence team develops large scale reporting tools, analytics, and supporting analytic/reporting data infrastructure for clients in energy, renewable resources, sustainability, and water sectors. They build high visibility tools used by project managers, data/sustainability scientists, analysts, and the AWS leadership team to make data-driven business decisions that directly impact AWS’s net-zero carbon and 100% renewable goals.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.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- 4+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience- Experience with data visualization using Tableau, Quicksight, or similar tools- Experience with data modeling, warehousing and building ETL pipelines- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling ...

If you love driving critical thinking and insight into challenging, unstructured problems and working with leaders in the organization to bring those insights into action, this role is for you. This is a hands-on role, however, being a part of a small team gives opportunity to take ownership of the customer / business problem across the spectrum from ideation to setting it up for implementation in partnership with stakeholder teams. Our Mission: We are powering an automation and self service driven customer journey for AWS customers leveraging a range of Analytics tools to generate business shaping insights. Analytics topics include, but not limited to:1. Product / Value Proposition design 2. Customer / Go-to-market 3. Customer Experience4. Business Planning & Forecasting Key job responsibilities- Develop, launch, and scale self-service analytics and insights offerings- 5+ years of relevant professional experience in business intelligence, analytics, statistics, data engineering, data science or related field.- Experience with Data modeling, SQL, ETL, Data Warehousing and Data Lakes.- Strong experience with engineering and operations best practices (version control, data quality/testing, monitoring, etc.)- Expert-level SQL- Proficiency with one or more general purpose programming languages (e.g. Python, Java, Scala, etc.)- Knowledge of AWS products such as Redshift, Quicksight- Excellent verbal/written communication & data presentation skills, including ability to succinctly summarize key findings and effectively communicate with both business and technical teams.About the teamThe Analytics team is a small, central group in the AWS Support organization. The team comprises members from a range of skill-sets such as strategy & planning, Machine Learning / predictive analytics and Business Intelligence. The Analytics team is responsible for pushing our Product, Process and Customer understanding and insight beyond the here and now to create value for the long-term. The team is responsible for coming up with hypotheses, uncovering key insights and developing a point of view on actions across the portfolio of our products and services. About AWS: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. BASIC QUALIFICATIONS- 5+ years of SQL experience- Experience programming to extract, transform and clean large (multi-TB) data sets- Experience with theory and practice of design of experiments and statistical analysis of results- Experience in scripting for automation (e.g. Python) and advanced SQL skills.- Experience with theory and practice of information retrieval, data science, machine learning and data mining ...

Come build the future of smart security with us. Are you interested in helping shape the future of devices and services designed to keep people close to what’s important?ABOUT RINGWe started in a garage in 2012 when our founder asked a simple question: what if you could answer the front door from your phone? What if you could be there without needing to actually, you know, be there? After many late nights and endless tinkering, our first Video Doorbell was born.That invention has grown into over a decade of groundbreaking products and next-level features. And at the core of all that, everything we’ve done and everything we’ve yet to build, is that same inventor's spirit and drive to bridge the distance between people and what they care about. Whatever it is, at Ring we’re committed to helping you be there for it.(https://www.ring.com)ABOUT THE ROLEThe Senior Data Scientist within Ring Data Science and Engineering plays a pivotal role in shaping how we carry the voice of our customers. We strive to understand their behaviors and preferences in order to provide them with the best experience connecting with the places, people and things that matter to them. This role will build scalable solutions and models to support our business functions (Subscriptions, Product, Customer Service). By leveraging a range of methods including statistical analysis and machine learning, you will explain, quantify, predict and prescribe in support of informing critical business decisions. You will translate business goals into agile, insightful analytics. You will seek to create value for both stakeholders and customers and inform findings in a clear, actionable way to managers and senior leaders.Key job responsibilities- Drive shared understanding among business, engineering, and science teams of domain knowledge of processes, system structures, and business requirements.- Apply domain knowledge to identify product roadmap, growth, engagement, and retention opportunities; quantify impact; and inform prioritization.- Advocate technical solutions to business stakeholders, engineering teams, and executive level decision makers.- Lead development and validation of state-of-the-art technical designs (data pipelines, data models, causal inference, predictive models, data insights/visualizations, etc)- Contribute to the hiring and development of others- Communicate strategy, progress, and impact to senior leadershipA day in the lifeTranslate/Interpret • Complex and interrelated datasets describing customer behavior, messaging, content, product design and financial impact.Measure/Quantify/Expand • Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance. • Analyze historical data to identify trends and support decision making. • Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters. • Provide requirements to develop analytic capabilities, platforms, and pipelines. • Apply statistical or machine learning knowledge to specific business problems and data.Explore/Enlighten • Formalize assumptions about how users are expected to behave, create statistical definition of the outlier, and develop methods to systematically identify these 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. • Make decisions and recommendations. • Build decision-making models and propose solution for the business problem you defined. • Conduct written and verbal presentation to share insights and recommendations to audiences of varying levels of technical sophistication. • Utilize code (Python/R/SQL) for data analyzing and modeling algorithms.BASIC QUALIFICATIONS- Bachelor's degree- 4+ years of data scientist 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- Experience with statistical models e.g. multinomial logistic regression- 5+ years of hands-on experience in modeling and analysis, and in deploying machine learning / deep learning models in production. ...

Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply cutting edge Generative AI algorithms to solve real world problems with significant impact? The AWS Industries Team at AWS helps AWS customers implement Generative AI solutions and realize transformational business opportunities for AWS customers in the most strategic industry verticals. This is a team of data scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI.The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train and fine tune the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and build applications to launch these solutions at scale. The AWS Industries team provides guidance and implements best practices for applying generative AI responsibly and cost efficiently.You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.In this Data Scientist role you will be capable of using GenAI and other techniques to design, evangelize, and implement and scale cutting-edge solutions for never-before-solved problems.Key job responsibilitiesAs a Data Scientist, you will-- Collaborate with AI/ML scientists, engineers, and architects to research, design, develop, and evaluate cutting-edge generative AI algorithms and build ML systems to address real-world challenges- Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production- Create and deliver best practice recommendations, tutorials, blog posts, publications, sample code, and presentations adapted to technical, business, and executive stakeholder- Provide customer and market feedback to Product and Engineering teams to help define product directionAbout the teamABOUT AWS: Diverse Experiences 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. 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.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 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 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 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- 5+ 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- Bachelor's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science ...

Are you inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Robotics. We are a smart team of doers who work passionately to apply cutting edge advances in robotics and software to solve real-world challenges that will transform our customers’ experiences. We invent new improvements every day. We are Amazon Robotics and we will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling, and fun. Amazon Robotics empowers a smarter, faster, more consistent customer experience through automation. Amazon Robotics automates fulfillment center operations using various methods of robotic technology including autonomous mobile robots, sophisticated control software, language perception, power management, computer vision, depth sensing, machine learning, object recognition, and semantic understanding of commands. Amazon Robotics has a dedicated focus on research and development to continuously explore new opportunities to extend its product lines into new areas.Key job responsibilitiesWe are seeking an enthusiastic Data Scientist to:- Design and implement state-of-the-art solutions for never-before-solved problems. - Collaborate closely with other research and robotics experts to design and run experiments, research new algorithms, and find new ways to improve Amazon Robotics analytics to optimize the Customer experience. - Partner with technology and product leaders to solve business problems using scientific approaches. - Build new tools and invent business insights that surprise and delight our customers. - Work to quantify system performance at scale, and to expand the breadth and depth of our analysis to increase the ability of software components and warehouse processes. - Work to evolve our library of key performance indicators and construct experiments that efficiently root cause emergent behaviors. - Engage with software development teams and warehouse design engineers to drive the evolution of the Amazon Robotics system, as well as the simulation engine that supports our work.A day in the lifeAs a member of the Software Research and Data Science (SWRDS) team, there are multiple different paths you can take. For example, you may conduct deep dive analysis of both structured and unstructured robotics field analyses. Some of our team members focus on modeling, pipelines and tooling work, while others focus more on analytic work. We also have team members working on early-concept solution analysis (leveraging simulations, ML-based models, experimenting with new solutions). About the teamThe Amazon Robotics Software Research and Data Science (SWRDS) team builds and runs simulation experiments and delivers analyses that are central to understanding the performance of the entire Amazon Robotics system. This includes operational and software scaling characteristics, bottlenecks, and robustness to “chaos monkey” stresses -- we inform critical engineering and business decisions about Amazon’s approach to robotic fulfillment.BASIC QUALIFICATIONS- Master's degree or higher in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or Bachelor's degree and 3+ years of professional or military experience- 1+ year of relevant academic research or industry experience within relevant science disciplines such as Machine Learning, Applied Statistics, Computer Vision, Optimization, or related field- 1+ year of experience using data querying languages (e.g. SQL), scripting languages (e.g. Python), or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) ...

AI is the most transformational technology of our time, capable of tackling some of humanity’s most challenging problems. That is why Amazon is investing in generative AI (GenAI) and the responsible development and deployment of large language models (LLMs) across all of our businesses. Come build the future of human-technology interaction with us. We are looking for a Research Scientist with strong technical skills which includes coding and natural language processing experience in dataset construction, training and evaluating models, and automatic processing of large datasets. You will play a critical role in driving innovation and advancing the state-of-the-art in natural language processing and machine learning. You will work closely with cross-functional teams, including product managers, language engineers, and other scientists.Key job responsibilitiesSpecifically, the Research Scientist will: • Ensure quality of speech/language/other data throughout all stages of acquisition and processing, including data sourcing/collection, ground truth generation, normalization, transformation, cross-lingual alignment/mapping, etc.• Clean, analyze and select speech/language/other data to achieve goals• Build and test models that elevate the customer experience • Collaborate with colleagues from science, engineering and business backgrounds• Present proposals and results in a clear manner backed by data and coupled with actionable conclusions• Work with engineers to develop efficient data querying infrastructure for both offline and online use casesBASIC QUALIFICATIONS- PhD, or Master's degree and 4+ years of quantitative field research experience- Experience investigating the feasibility of applying scientific principles and concepts to business problems and products- Experience in Python, Perl, or another scripting language- Experience with various machine learning techniques and parameters that affect their performance- Experience analyzing both experimental and observational data sets ...

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 ...

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 ROLEAudible's insights team leverages data to create value for our company and customers. We're seeking a Data Science Lead for our marketing and product measurement science team, to help us understand the return on investment (ROI) of our paid media and brand investments.As a Data Science Lead, you’ll manage a team of scientists working in the media measurement space. Your primary focus will be guiding scientific approach in developing and deploying advanced marketing measurement models (e.g., lifetime value, media mix). You will also lead Audible's scaled experimentation program, maintaining scientific integrity in global paid media experiments and guiding meta-analytical work to assess program health. Additionally, you will serve as the primary scientific contact for third-party media partners (Meta, Google), collaborating with them on new measurement approaches. You'll work with Audible marketers to translate sophisticated scientific methodologies into actionable business strategies, ultimately driving more effective marketing investments.ABOUT YOUAs a Data Science Lead, you will provide technical leadership in marketing measurement, design scalable model solutions, collaborate across scientific disciplines, communicate complex concepts clearly, and mentor team members to drive collective success.You have deep technical expertise across statistical modeling, machine learning, causal inference, and experimental design. You demonstrate a strong understanding of experimental design and evaluation. You are an expert in statistical modeling techniques. You have deep experience solving marketing-related problems, such as customer acquisition, retention, and ROI.You possess a strong ownership mindset and the ability to guide a technical team with minimal oversight. Your innovative problem-solving skills thrive in ambiguous environments, and you excel at translating complex scientific concepts into actionable insights. Outstanding business acumen, coupled with the ability to manage multiple projects simultaneously, defines your professional approach.You are committed to building a positive team culture, reliably delivering against commitments, and have a genuine passion for mentoring and developing scientific talent. You are adaptable across different scientific approaches and comfortable collaborating with cross-disciplinary scientific teams.As a Data Science Lead, you will...- Be a technical leader of other scientists, with substantial scope, impact, and visibility in the marketing measurement space- Understand complex use cases across the business and design scalable, efficient, automated model solutions, including developing, delivering, and improving various marketing measurement models- Collaborate with economists, applied scientists, and other data scientists on the right model specification(s) to serve business needs in the context of paid media measurement- Communicate clearly with senior audiences, translating complex scientific concepts into simplified, relevant outputs that can be quickly understood and actioned by both technical and non-technical colleagues- Mentor and grow scientists in your team and across AudibleABOUT 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- 3+ years managing a team of scientists or engineers, with a proven track record of hiring and developing junior team members- Master’s degree in relevant discipline and 5+ years of relevant professional experience (or equivalent)- Hands-on experience with marketing measurement models, including experience with articulating modeling trade-offs to business partners- Hands-on experience in designing and evaluating experiments, including experience with formal meta-analytical approaches for evaluating programs of experimentation- Hands-on experience with successfully putting marketing models into production- Fluency in Python and SQL- Experience influencing and delivering on a science roadmap ...

The Mission of Amazon's Artificial General Intelligence (AGI) team is to "Build world-class general-purpose intelligence services that benefits every Amazon business and humanity." Are you a data enthusiast? Are you a creative big thinker who is passionate about using data to direct decision making and solve complex and large-scale challenges? If so, then this position is for you! We are looking for a motivated individual with strong analytical and communication skills to join us.In this role, you will apply advanced analytics techniques, AI/ML, and statistical concepts to derive insights from massive datasets. The ideal candidate should have expertise in AI/ML, statistical analysis, and the ability to write code for building models and pipelines to automate data and analytics processing. They will help us design experiments, build models, and develop appropriate metrics to deeply understand the strengths and weaknesses of our systems. They will build dashboards to automate data collection and reporting of relevant data streams, providing leadership and stakeholders with transparency into our system's performance. They will turn their findings into actions by writing detailed reports and providing recommendations on where we should focus our efforts to have the largest customer impact. A successful candidate should be a self-starter, comfortable with ambiguity with strong attention to detail, and have the ability to work in a fast-paced and ever-changing environment. The ideal candidate should possess excellent verbal and written communication skills, capable of effectively communicating results and insights to both technical and non-technical audiencesBASIC QUALIFICATIONS- 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 data scientist experience- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience- Bachelor's degree- Experience diving into data to discover hidden patterns and of conducting error/deviation analysis- Knowledge of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc. ...

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 ...

The Private Brands Discovery team designs innovative machine learning solutions to enhance customer awareness of Amazon’s own brands and help customers find products they love. This interdisciplinary team of scientists and engineers incubates and develops disruptive solutions using cutting-edge technology to tackle some of the most challenging scientific problems at Amazon. To achieve this, the team utilizes methods from Natural Language Processing, deep learning, large language models (LLMs), multi-armed bandits, reinforcement learning, Bayesian optimization, causal and statistical inference, and econometrics to drive discovery throughout the customer journey. Our solutions are crucial to the success of Amazon’s private brands and serve as a model for discovery solutions across the company.This role presents a high-visibility opportunity for someone eager to make a business impact, delve into large-scale problems, drive measurable actions, and collaborate closely with scientists and engineers. As a team lead, you will be responsible for developing and coaching talent, guiding the team in designing and developing cutting-edge models, and working with business, marketing, and software teams to address key challenges. These challenges include building and improving models for sourcing, relevance, and CTR/CVR estimation, deploying reinforcement learning methods in production etc.In this role, you will be a technical leader in applied science research with substantial scope, impact, and visibility. A successful team lead will be an analytical problem solver who enjoys exploring data, leading problem-solving efforts, guiding the development of new frameworks, and engaging in investigations and algorithm development. You should be capable of effectively interfacing between technical teams and business stakeholders, pushing the boundaries of what is scientifically possible, and maintaining a sharp focus on measurable customer and business impact. Additionally, you will mentor and guide scientists to enhance the team's talent and expand the impact of your work.BASIC QUALIFICATIONS- 3+ years of scientists or machine learning engineers management experience- Knowledge of ML, NLP, Information Retrieval and Analytics- Expert in developing large-scale ML systems in a production environment- Extensive experience applying theoretical models in an applied environment- Demonstrated proficiency in deep learning models, experience building production level causal inference models- Expert in more than one more major programming / scripting languages (Python, Scala, PySpark or similar)- Excellent written and verbal communication skills while addressing both technical and business people; ability to speak at a level appropriate for the audience.- Experience coaching and reviewing work of junior ML Scientists, making great hiring decisions. ...

Do you like helping U.S.Federal agencies implement innovative cloud computing solutions and solve technical problems? Would you like to do this using the latest cloud computing technologies? Do you have a knack for helping these groups understand application architectures and integration approaches, and the consultative and leadership skills to launch a project on a trajectory to success? Amazon Web Services (AWS) 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 strong success for the Customer. 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.We are looking for an experienced, self-driven Data Analytics Consultant. In this role, you will be building complex data engineering and business intelligence applications using AWS big data stack. You should have deep expertise and passion in working with large data sets, data visualization, building complex data processes, performance tuning, bringing data from disparate data stores and programmatically identifying patterns. You should have excellent business acumen and communication skills to be able to work with business owners to develop and define key business questions and requirements. It is expected to work from one of the above locations (or customer sites) at least 1+ days in a week. This is not a remote position. You are expected to be in the office or with customers as needed.This position requires that the candidate selected must currently possess and maintain an active TS/SCI security clearance with polygraph. The position further requires the candidate to opt into a commensurate clearance for each government agency for which they perform AWS work.Key job responsibilities• Design, implement, and support data warehouse/ data lake infrastructure using AWS bigdata stack, Python, Redshift, QuickSight, Glue/lake formation, EMR/Spark, Athena etc.• Develop and manage ETLs to source data from various financial, AWS networking and operational systems and create unified data model for analytics and reporting.• Creation and support of real-time data pipelines built on AWS technologies including EMR, Glue, Redshift/Spectrum and Athena.• Collaborate with other Engineering teams, Product/Finance Managers/Analysts to implement advanced analytics algorithms that exploit our rich datasets for financial model development, statistical analysis, prediction, etc.• Continual research of the latest big data and visualization technologies to provide new capabilities and increase efficiency.• Use business intelligence and visualization software (e.g., QuickSight) to develop dashboards those are used by senior leadership. • Empower technical and non-technical, internal customers to drive their own analytics and reporting (self-serve reporting) and support ad-hoc reporting when needed.• Working closely with team members to drive real-time model implementations for monitoring and alerting of risk systems.• Manage numerous requests concurrently and strategically, prioritizing when necessary• Partner/collaborate across teams/roles to deliver results.• Mentor other engineers, influence positively team culture, and help grow the team.About the teamDiverse ExperiencesAWS 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 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. BASIC QUALIFICATIONS- 3+ years of data engineering experience- Experience with data modeling, warehousing and building ETL pipelines- Experience with SQL- Bachelor's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent ...

The Device, Digital & Alexa Support (D2AS) team seeks a Data Scientist to drive our hiring process improvements. In this role, you will:- Lead modeling projects to enhance our hiring pipeline efficiency and candidate experience.- Develop data-driven insights to inform product decisions.- Design and conduct statistical experiments to uncover hiring optimization opportunities.- Create user-friendly analytical tools for our product team.The ideal candidate will have:- Strong leadership and project management skills.- Experience in data requirements gathering and statistical methodology development. - Ability to balance technical expertise with business acumen - Creativity in problem-solving, backed by statistical evidence.Your work will directly impact our ability to attract and retain top talent, ultimately benefiting our customers through improved support services. Join us in simplifying and enhancing our hiring process with data-driven solutions.Key job responsibilities- Design and run experiments, research new algorithms, and find new ways to improve hiring analytics to optimize the candidate and associate experience. - Research machine learning algorithms and implement by tailoring to business needs and test on large datasets. - Partner with scientists, engineers and product leaders to solve business and technology problems using scientific approaches to build new services that surprise and delight our customers. - Collaborate with BI/Data Engineer teams and drive the collection of new data and the refinement of existing data sources to continually improve data quality. - Foster culture of continuous engineering improvement through mentoring, feedback, and metrics. - Manipulating/mining data from databases (Redshift, SQL Server, Oracle DW, and Salesforce). - Providing analytical network support to improve quality and standard work results.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 environment.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!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 teamWe at D2AS strive to make digital experiences effortless for customers. Our goal is to anticipate, evaluate, prevent, and eliminate any effort required from customers. We achieve this by setting the strategy for digital support and accelerating the delivery of seamless support experiences across Amazon's digital products.Our team combines strategic thinking, technology expertise, and customer experience best practices. This ensures customers can easily get the most value from Amazon's digital offerings. We focus on providing the right support at the right time, tailored to each customer's needs. By eliminating friction and making support effortless, we enhance the overall customer experience.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 ...

If you are interested in this position, please apply on Twitch's Career site https://www.twitch.tv/jobs/en/About Us:Twitch is the world’s biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more. It is where thousands of communities come together for whatever, every day.We’re about community, inside and out. You’ll find coworkers who are eager to team up, collaborate, and smash (or elegantly solve) problems together. We’re on a quest to empower live communities, so if this sounds good to you, see what we’re up to on LinkedIn and X, and discover the projects we’re solving on our Blog. Be sure to explore our Interviewing Guide to learn how to ace our interview process.About the RoleData is central to Twitch's decision-making process, and data scientists are a critical component to evangelize data-driven decision making in all of our operations. As a data scientist at Twitch, you will be on the ground floor with your team, shaping the way product performance is measured, defining what questions should be asked, and scaling analytics methods and tools to support our growing business, leading the way for high quality, high velocity decisions for your team. For this role, we're looking for an experienced product data scientist who will help develop the strategy and evaluate/improve product initiatives within our Creator product team. You will be responsible to define and track KPIs, design experiments, evaluate A/B tests, implement data instrumentation, and inform on investment. Our ideal candidate is a "full-stack" data powerhouse who uses data to drive decision making to make the best products for our creators and their communities. Your input will be core to decision making across all major product strategies and initiatives that our team builds. You will work closely with product managers, technical program managers, engineering, data scientists, and organization leadership within and outside of the Creator organization. You Will- Inform product strategies by defining and updating core metrics for each initiative- Establish analytical framework for your team: ad-hoc analysis, automated dashboards, and self-service reporting tools to surface key data to stakeholders - Evaluate and forecast impact of product features on creators, viewers, and the entire Twitch ecosystem- Design A/B experiments to drive product direction with iterative innovation and measurement- Drive the team's analysis roadmap and prioritize the most valuable projects- Tackle complex and ambiguous analytic projects, resolve ambiguity and accurately identify the trade-offs between speed and quality and apply or route work as necessary- Dive deep into the data to understand how creator and viewer behaviors change with the evolution of our product- Act as our team's thought leader on best practices and move towards long-term vision of sustainable and thriving data processes - Own data collection and product instrumentation implementation and quality assurance- Work hand-in-hand with business, product, engineering, and design to proactively influence and inform teammates' decisions throughout the product life cycle- Distill ambiguous product or business questions, find clever ways to answer them, and to quantify the uncertaintyPerks- Medical, Dental, Vision & Disability Insurance- 401(k)- Maternity & Parental Leave- Flexible PTO- Amazon Employee DiscountAbout the teamTwitch is all about community, and our Community Team is a core pillar of what makes Twitch, Twitch. Teams within Community are responsible for a myriad of product areas impacting the creator, viewer, and moderator journeys on our platform. As a member of our team, you'll build solutions that improve g the experience of millions of daily active users on our platform and create tools that keep both streamers and viewers engaged and connected on our platform. BASIC QUALIFICATIONS- BA/BS in Analytics, Data Science, Computer Science, Mathematics, or equivalent industry experience- 3+ years of experience as a data scientist or data analyst in a high velocity, data-driven environment- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience- Expert SQL skills and proficiency in Python/R- Experience using data to create insight, drive business decisions and influence leadership ...

At OpsTech Solutions (OTS), we are a technology centric services organization that designs, builds, and sustains the invisible, high-quality network, compute infrastructure and device scaffolding that empowers and protects Amazon’s global Operations.The OTS DataTech team drives the enterprise data strategy, focusing on Data as a Product and supporting OTS-wide efforts, including generative AI and machine learning capabilities to fuel innovation and automation across the OTS product portfolio.Key job responsibilitiesAs a Sr Data Engineer on the DataTech team, you will play a critical role in designing and building the foundational data infrastructure components that empowers OTS product teams with business critical metrics, develop systems and tools to ingest data from diverse data sources, enable seamless data publish, subscribe, and self-service analytics for business metrics reporting. You will participate in automation of data governance and data quality monitoring processes, support data needs for AI/ML and Gen AI capabilities.A day in the lifeOn a day to day you will build and operate a highly scalable data mesh infrastructure that support data needs for OTS organization through self service Data as a Product. 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 ...

The CATALST NLP Services team within the Selling Partner Services (SPS) Core Services organization is responsible for simplifying multi-lingual experiences for our customers. We build and leverage various AI services to eliminate language barriers at scale through Machine Translation for Amazon Customers and Sellers WW across 30+ programs within SPS and customers outside of SPS. We leverage state-of-the-art NLP solutions including Large Language Models, Machine Translation, Language Detection, and OCR to provide a full suite of content analysis capabilities. Our customers include Selling Partners, Buyers, Amazon Associates, Amazon Investigators, and various Science teams.In this role, you will be a key owner within our cross-disciplinary team that includes Product Managers, Software Engineers, and Applied Scientists and execute on our 3 Year Plan. You will pioneer new technologies in NLP, machine translation, and machine learning. You will have ownership of the end-to-end development of solutions to complex problems from design to implementation and you will play an integral role in strategic decision-making. You will also work closely with other stakeholders such as engineers, operations teams and product owners to build ML pipelines, platforms and solutions that solve business problems.Key job responsibilities* Participate in the design, development, evaluation, deployment and updating of automated and scalable machine learning models, with a focus on machine translation* Develop and/or apply statistics, NLP and machine learning experiments and methodologies to different applications* Work closely with Scientists and Software Engineers on experimentations, evaluation and implementation* Work closely with business partners to understand the goals and develop solutions to achieve such goalsBASIC QUALIFICATIONS- Experience programming in Java, C++, Python or related language- Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse ...

Are you interested in shaping the future of Advertising and B2B Sales? We are a growing science and engineering team with an exciting charter and need your passion, innovative thinking, and creativity to help take our products to new heights.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 are strategically important to our businesses driving long term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!Within the Advertising Sales organization, we are building a central AI/ML team and are seeking top science talent to build new, science-backed services to drive success for our customers. Our goal is to transform the way account teams operate by creating actionable insights and recommendations they can share with their advertising accounts, and ingesting Generative AI throughout their end-to-end workflows to improve their work efficiency.As a part of our team, you will bring deep expertise in quantitative modeling (forecasting, recommender systems, reinforcement learning, causal inferencing or generative artificial intelligence) to build and refine models that create actionable insights for the business. You will be a thought leader as we chart new courses with our ad sales support technologies, and you have the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers. As a senior lead, you will have the excitement to take iterative approaches to tackle big, long-term problems.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 ads 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; this is your opportunity to work within the fastest growing businesses across all of Amazon! Define a long-term scientific vision for our advertising sales business, driven from our customers' needs, translating that direction into specific plans for scientists, engineers and product teams. This role combines scientific leadership, organizational ability, technical strength, product focus, and business understanding.Key job responsibilities- Build statistical and AI/ML models to generate actionable insights for the business- Partner with product and engineering teams to test and measure the success of implemented AI/ML models- Lead reviews with senior leadership, deep dive model outputs and explain implications of model recommendations.- Interact with our sales customers to understand the business problem, help and aid them in implementation of AI/ML based solutions, deliver briefing and deep dive sessions to customers, and guide customer on adoption patterns and paths to production- Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholders- Provide customer and market feedback to Product and Engineering teams to help define product directionAbout the teamSales AI is a central science and engineering organization within Amazon Advertising Sales that powers selling motions and account team workflows via state-of-the-art of AI/ML services. Sales AI is investing in a range of sales intelligence models, including the development of advertiser insights, recommendations and Generative AI-powered applications throughout account team workflows.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- 4+ years of data scientist experience- Experience with statistical models e.g. multinomial logistic regression ...

AWS Hardware Engineering is looking for an experienced, innovative Data Engineer to join their Data Science and Analytics team. You will be part of a group of talented engineers and scientists that builds data products and services to turn hardware monitoring data into insights using advanced analytics and machine learning.As a Data Engineer, you will provide technical leadership, lead data engineering initiatives, and build end-to-end analytical solutions that are highly available, scalable, stable, secure, and cost-effective. You strive for simplicity, demonstrate creativity and sound judgement. You deliver data solutions that are customer focused, easy to consume and create business impact.You are passionate about working with huge datasets and have experience with the organization and curation of data for analytics. You have a strategic and long-term view on architecting advanced data ecosystem. You are experienced in building efficient and scalable data services and can integrate data systems with AWS tools and services to support a variety of customer use cases/applications.In this role, you can:Design, implement and operate large-scale, high-volume, high-performance data structures for analytics and data science.Implement data ingestion routines both real time and batch using best practices in data modeling, ETL/ELT processes by leveraging AWS technologies and big data tools.Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions with a flexible and adaptable data architecture.Collaborate with engineers to help adopt best practices in data system creation, data integrity, test design, analysis, validation, and documentation.Collaborate with scientists to create fast and efficient algorithms that exploit our rich data sets for optimization, statistical analysis, prediction, clustering, and machine learning.Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service modeling and production support for customers.This role falls within the broader AWS Infrastructure Services (AIS) organization, which 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 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.About the teamAmazon 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.AWS values diverse experiences. Even if you do not meet all 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- A Bachelor's degree in a quantitative/technical field (e.g. Computer Science, Statistics, Engineering) or equivalent industry experience- 3+ years of experience with demonstrated strength in ETL/ELT, data modeling, data warehouse technical architecture, infrastructure components and reporting/analytic tools- 3+ years of hands-on experience in writing complex, highly-optimized SQL queries across large data sets.- 3+ years of experience in scripting languages like Python etc. ...

The People eXperience and Technology (PXT) Central Science Team uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. We are an interdisciplinary team which combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. We invest in innovation and rapid prototyping of scientific models and software solutions to accelerate informed, accurate, and reliable decision backed by science and data.We are looking for an experienced data engineer engineer to integrate data sources and create a data infrastructure to model and research all aspects of HR, including: workforce planning, recruiting, employee engagement, retention, development, employee benefits, and compensation. Lead information architecture workstream, automate ingestion and consumption using AWS toolsets and data mesh implementations. Build data taxonomy to organize data by subject matter domains. Develop a seamless vending strategy for sharing data with PXT and Amazon stakeholders. Lead data curation for easy consumption in science models. Lead and streamline data governance for protecting privacy for Amazonians. The ideal candidate is expected to work closely with senior scientists and business leaders to study the impact Amazon has had on workers, the market, and the economy. You will build new data engineering solutions end-to-end, will work with multiple stakeholders across HR and Operations, and will build data pipelines/automation that can be used by distributed systems to run statistical and ML models. A successful candidate will have a passion for innovation, interest in cutting-edge technology, and excitement about working in a high-impact domain.BASIC QUALIFICATIONS- 3+ years of data engineering experience- Experience with data modeling, warehousing and building ETL pipelines- Experience with SQL ...

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, engineers, supply chain specialists, security experts, product and 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.Do you have a desire to make a major contribution to the future in the rapid growth environment of Cloud Computing? Amazon Web Services is looking for a Sr Data Engineer to help build a scalable and robust platforms that supports the AWS Infrastructure Supply Chain Finance (SCF) organization. You will be part of the Finance Automation and Analytics team working with Product managers, Business intelligence engineers, Business Analysts and other Data Engineers to architect the systems in context with the business outcomes.You will have a passion to dive deep, a high level of customer focus and a track record in process improvement. This role requires an individual with excellent analytical abilities, strong knowledge of data engineering solutions and the ability to work with Finance, quantitative and business teams. You will lead multiple automation and controllership initiatives across the Finance org. You will be primarily using but not limited to AWS solution stacks like Redshift, S3, Glue, Lambda, SNS, SQS, Cloudwatch, EC2, Lambda, Data pipeline and reporting tools such as Tableau and Alteryx/KNIME to implement solutions. You will be responsible for the full software development life cycle to build scalable application and deploy in AWS Cloud. 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.- Collaborate with Finance, Tax, Supply Chain, Procurement, and Engineering to capture requirements and deliver analytics solutions. - Able to read, write, and debug data processing and orchestration code written in SQL/Python following best coding standards (e.g. version controlled, code reviewed, etc.)- Apply automation so that with every iteration on a problem, you build your solution to have maximum scale and self-service ability by stakeholders. - Understand a broad range of Amazon’s data resources and know how, when, and which to use and which not to use.- Participate in strategic and tactical planning discussions to interface with business customers, gathering requirements and delivering complete reporting solutions.BASIC QUALIFICATIONS- 7+ 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- Knowledge of distributed systems as it pertains to data storage and computing- Experience building data products incrementally and integrating and managing data sets from multiple sources ...