Data Science

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 supports OTS-wide data and analytics efforts, including generative AI and machine learning capabilities to fuel innovation and automation across the OTS product portfolio.Key job responsibilitiesAs a 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, process data from diverse data sources, data lakes, enable seamless data publish and subscribe, and self-service analytics for business metrics reporting. You will participate in automation of data governance processes and data quality monitoring, support data needs for AI/ML capabilities.A day in the lifeOn a day to day you will build and operate a highly scalable data mesh infrastructure, data lake that hosts OTS data and provide access through Data as a Product. BASIC QUALIFICATIONS- 3+ years of data engineering experience- Experience with data modeling, warehousing and building ETL pipelines ...

Are you excited about the prospect of making it easier for builders to innovate and create great software? If so, Amazon Software Builder Experience (ASBX) may be the place for you. Created in 2022, ASBX has the mission of creating the world’s best builder experience across tens of thousands of software engineers across both Amazon and AWS.Builder Insights works at the core of ASBX, shaping what it means to create the world’s best software builder experience. How do we reduce friction and toil for builders, enabling them to have more time to build features and capabilities that will delight Amazon’s customer? Where should we invest in tooling, automation, knowledge discovery, training, etc. to create the biggest benefits for builders? How do we inform managers what “good” looks like compared to teams similar to them? These are just a few of the challenges we are tackling right now.We are looking for a passionate and hardworking scientist to use data to discover insights and turn those insights into actionable recommendations and products that improve the experience of builders across Amazon. As a data scientist on the Builder Insights team, you will help conduct rigorous science for the organization, with a focus on discovery, research, and application of generated insights into science-enabled products and features. You will have exposure to senior leadership as we communicate results and provide scientific guidance to the business. This role will also collaborate with scientists across organizations to influence science roadmaps and disseminate research.You will work with engineers to onboard data, perform scientifically rigorous insight discovery and research, and develop the right statistical and machine learning model-based solutions to deliver impact for builders. You will solve ambiguous problems, working with stakeholders to determine the right questions to ask and developing the roadmap for delivering results. You will apply analytical abilities, business understanding, and technical expertise to identify specific and actionable opportunities to solve existing business problems and look around corners for future opportunities. You will synthesize and communicate insights and recommendations to audiences of varying levels of technical sophistication to influence investment into builder experience improvements through data-backed solutions.*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.10025Key job responsibilities• Lead projects, requiring both business and technical domain knowledge, and drive solutions to complex or ambiguous problems with limited guidance.• Create models and analyses that affect important business decisions.• Review analyses of other scientists and provide feedback.• Employ scientifically rigorous standards across multiple data science disciplines, knowing what trade-offs to make to deliver results.• Build models using Python, R, etc. (and ability to access data using Spark, SQL, or similar)• Proficiently use at least one common data science language to develop models (Python, R, etc.) and process data (Spark, SQL, etc.).• Communicate verbally and in writing to business customers with various levels of technical knowledge, educating them about our systems, as well as sharing insights and recommendationsA day in the life*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.**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.**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.**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 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. About the teamThe data science team in Builder Insights believes Are Right, A Lot means listening to diverse points of view and building a culture of inclusivity where every team member can contribute. It's only when we work together and include everyone that the best ideas can shine through, and that's when we have the most impact for our customers. You can let your Ownership shine on this team! - we wear different hats, getting involved with product strategy, building infrastructure, and everything in between. We have an innate desire to Learn & Be Curious and Dive Deep as engineers and scientists.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. 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 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. 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. Mentorship and 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. 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.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 ...

Want to be part of a team that is helping redefine the future of video advertising? Prime Video is looking for a world-class Science & Analytics Leader to help us assemble and execute against our team’s strategic advertising initiatives and change how advertisers engage with consumers via streaming media around the world. Video Advertising is rapidly evolving as customers shift their viewing experiences from traditional linear TV to streaming via connected devices. Prime Video is a rising player in this space. We have differentiated assets in terms of consumer experiences and audience insights against a breadth of exclusive content which positions us well for the long-term. We are seeking a Science & Analytics Leader to manage the development and application of methods to: examine the complex data flows of the Prime Video Advertising, translate deep-dives into actionable insights for our product teams; and build new tools and services in order to dynamically optimize the business with customers and advertisers. In this role, you and your teams will analyze our advertising-related data to enable sound business insights ongoing while also helping to improve the performance of our packaging and ad serving decisions. This will need to take into account advertiser demand and customer engagement expectations, desired targeting and relevance outcomes, and the adoption and impact of new ad product releases.Key job responsibilities• Analyze data trends regarding supply/demand optimization, ad load, and mix effects that affect advertiser objectives and customer experience. • Provide analysis to senior leaders on issues like business impact of new feature development, addressability or recognition rates, and changes of ad serving systems to improve monetization rate and customer experience - highlighting insights that will inform our business development and engineering roadmaps. • Formalize our approach to balancing CX and yield optimization by analyzing supply and demand patterns across multiple channels and products. • Identify, standardize, and operationalize KPIs to effectively measure the performance of all systems involved in ad serving, and use trend insights to inform business priorities. • Partner with engineering teams to define data logging requirements and get these prioritized in engineering roadmaps. • Validate financial models through analysis • Develop and own ad revenue and supply intelligence analytics decks that provide ongoing deep-dives or low-touch insights.A day in the lifeThe Science & Analytics Leader will work closely with business leaders and engineers on developing common data architecture that will optimize our data logging at different grains, and will allow data interoperability from bid flow to optimization to campaign delivery. The candidate will then analyze the data and present papers and ongoing reports on actionable insights, as well as science-powered models for optimizing against those insights at scale. In addition, we will be looking for the candidate to attract and develop a high-impact, multi-functional data analytics team. About the teamThe Prime Video Advertising Science & Analytics team works in close alignment with PM, engineer, business, and sales teams to help achieve advertiser objectives against best-in-class customer ad experiences, and meaningfully improve financial performance. We pride ourselves for acting as owners of the areas we support, and thinking broadly about the impact that our analysis, audits, and models bring to the business. We are at our best when we understand not just the analytics components of our business, but also have deep business knowledge of customer needs and product operations.BASIC QUALIFICATIONS- Master’s degree or PhD in a field that has significant emphasis on quantitative methods such as statistics, or mathematical optimization - Solid business judgment capable of driving an organization to the right results with a focused, pragmatic, approach to data analytics - Experience operating successfully in a fast-paced, results-oriented environment, and having the ability to influence the decisions of senior business leaders through effective verbal and written communication, logical reasoning, and the presentation of alternatives- Close familiarity and understanding of RTB/DTB supply data including the systems and processes required to turn a bid request from a publisher into an ad seen by a person- Track record of mentoring and growing an impactful data analytics team ...

Do you have a passion for data? Are you matriculating in a Master’s or PhD program? Amazon is looking for driven data science students with strong modeling skills who are comfortable owning and executing data. To be successful in this internship, you will need the ability to develop, automate, and run analytical models for our systems. During this internship, you will build tools and support structures needed to analyze and dive deep into data to resolve systems errors and changes. You will have the ability to present your findings to our business partners and help drive improvements.Previous applicants demonstrated the aptitude to manage medium-scale modeling projects, identified requirements, and built methodology/tools that were statistically grounded.For more information on the Amazon Science community please visit https://www.amazon.scienceBASIC QUALIFICATIONS- Are 18 years of age or older- Work 40 hours/week minimum and commit to 12 week internship maximum- Can relocate to where the internship is based- Experience with data scripting languages (e.g. SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)- Experience in data science, machine learning or data mining- Experience with big data: processing, filtering, and presenting large quantities (100K to Millions of rows) of data- Must be actively enrolled in a Master's or PhD program ...

Our team's mission is to improve Shopping experience for customers interacting with Amazon devices via voice. We research and develop advanced state-of-the-art speech and language modeling technologies. Do you want to be part of the team developing the latest technology that impacts the customer experience of ground-breaking products? Then come join us and make history.Key job responsibilitiesWe are looking for a passionate, talented, and inventive Applied Scientist with a background in Machine Learning to help build industry-leading Speech and Language technology.As an Applied Scientist at Amazon you will work with talented peers to develop novel algorithms and modelling techniques to drive the state of the art in speech synthesis.Position Responsibilities:* Participate in the design, development, evaluation, deployment and updating of data-driven models for Speech and Language applications.* Participate in research activities including the application and evaluation of Speech and Language techniques for novel applications.* Research and implement novel ML and statistical approaches to add value to the business.* Mentor junior engineers and scientists.BASIC QUALIFICATIONS- Experience developing experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations- PhD- Experience in Python, Perl, or another scripting language ...

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.Are you interested in building highly impactful business intelligence (BI) solutions in a mixed team of BIEs, Data Scientists, Data Engineers, and SDEs? If so, you should consider a role in AWS Hardware Engineering Services.We are responsible for designing, qualifying, and maintaining server solutions for AWS and its customers. The Data Science and Analytics team supports the broader Hardware Engineering organization by acting as conduits between the data and the business. As a Business Intelligence Engineer in our team, you will support the design, implementation, and delivery of BI solutions in a complex problem space that has a long-term impact on a business, organization, and technology. You will gain exposure to both Data Science and Data Engineering disciplines, while developing your technical skills and leadership ability. The ideal candidate will be experienced in the areas of data and business intelligence systems. You have a demonstrated record of driving new analytical solutions from inception to launch. You are highly skilled with SQL, have experience developing ETL processes, understand data visualization tools such as QuickSight, and have familiarity with at least one scripting language.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.Amazon Web Services (AWS) values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.BASIC QUALIFICATIONS- 5+ years of experience in analyzing, interpreting and reporting data- Experience with data visualization using Tableau, Quicksight, or similar tools- Experience with data modeling, warehousing and building ETL pipelines- Experience in Statistical Analysis packages such as R, SAS and Matlab- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling- Experience working directly with business stakeholders to translate between data and business needs ...

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. ...

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

The Private Brands team is looking for an Applied Scientist to join the team in building science solutions at scale. Our team applies Optimization, Machine Learning, Statistics, Causal Inference, and Econometrics/Economics to derive actionable insights. We are an interdisciplinary team of Scientists, Engineers, and Economists and primary focus on building optimization and machine learning solutions in supply chain domain with specific focus on Amazon private brand products.Key job responsibilitiesYou will work with business leaders, scientists, and economists to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable optimization solutions and ML models.This is a unique, high visibility opportunity for someone who wants to have business impact, dive deep into large-scale problems, enable measurable actions on the consumer economy, and work closely with scientists and economists. As a senior scientist, you bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions.We are particularly interested in candidates with academic and/or practical background in Operations Research and Machine Learning. Experience in applying Operations Research and/or ML to supply chain problems is a plus.BASIC QUALIFICATIONS- 5+ 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- Experience with conducting research in a corporate setting ...

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 ...

Amazon.com’s Buyer Risk Prevention's (BRP) mission is to make Amazon the safest and most trusted place worldwide to transact online. BRP safeguards every financial transaction across all Amazon sites. As such, BRP designs and builds the software systems, risk models, and operational processes that minimize risk and maximize trust in Amazon.com. The BRP organization is looking for an Applied Scientist for the Buyer Abuse team, whose mission is to combine advanced analytics with investigator insight to create mechanisms to proactively and reactively reduce the impact of abuse across Amazon. Key job responsibilitiesAs an Applied Scientist, you will be responsible for modeling complex problems, discovering insights, and building cutting edge risk algorithms that identify opportunities through statistical models, machine learning, and visualization techniques to improve operational efficiency and reduce monetary losses and improve customer trust. You will need to collaborate effectively with business and product leaders within BRP and cross-functional teams to build scalable solutions against high organizational standards. The candidate should be able to apply a breadth of tools, data sources, and ML techniques to answer a wide range of high-impact business questions and proactively present new insights in concise and effective manner. The candidate should be an effective communicator capable of independently driving issues to resolution and communicating insights to non-technical audiences. This is a high impact role with goals that directly impacts the bottom line of the business. Responsibilities: - Invent, implement, and deploy state of the art machine learning algorithms and systems - Build prototypes and explore conceptually new solutions - Define and conduct experiments to validate/reject hypotheses, and communicate insights and recommendations to Product and Tech teams - Take ownership of how ML solutions impact Amazon resources and Customer experience - Develop efficient data querying infrastructure for both offline and online use cases - Collaborate with cross-functional teams from multidisciplinary science, engineering and business backgrounds to enhance current automation processes - Learn and understand a broad range of Amazon’s data resources and know when, how, and which to use and which not to use. - Research and implement novel machine learning and statistical approaches - Maintain technical document and communicate results to diverse audiences with effective writing, visualizations, and presentationsPlease visit https://www.amazon.science for more informationBASIC QUALIFICATIONS- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

The Supply Chain Optimization Technologies (SCOT) team builds technology to automate and optimize Amazon’s supply chain of physical goods. We seek a Data Scientist with strong analytical and communication skills to join our team. SCOT manages Amazon's inventory under uncertainty of demand, pricing, promotions, supply, vendor lead times, and product life cycle. We optimize complex trade-offs between customer experience, inventory costs, fulfillment costs, fulfillment center capacity, etc. We develop sophisticated algorithms that involve learning from large amounts of data such as prices, promotions, similar products, and other data from our product catalog in order to automatically act on millions of dollars’ worth of inventory weekly and establish plans for tens of thousands of employees. As a Data Scientist, you will contribute to the research community, by working with other scientists across Amazon and our Supply Chain, as well as collaborating with academic researchers and publishing papers both internally and externally.Key job responsibilitiesMajor responsibilities include: - Analysis of large amounts of data from different parts of the supply chain and their associated business functions - Improving upon existing machine learning methodologies by developing new data sources, developing and testing model enhancements, running computational experiments, and fine-tuning model parameters for new models - Formalizing assumptions about how models are expected to behave, creating definitions of outliers, developing methods to systematically identify these outliers, and explaining why they are reasonable or identifying fixes for them - Communicating verbally and in writing to business customers with various levels of technical knowledge, educating them about our research, as well as sharing insights and recommendations - Utilizing code (Python, R, Scala, etc.) for analyzing data and building statistical and machine learning models and algorithmsA day in the lifeAs a Data Scientist in SCOT, you will be tasked to understand and work with cutting edge research to enable the implementation of sophisticated models on big data. As a successful data scientist in the SCOT team, you are an analytical problem solver who enjoys diving into data from various businesses, is excited about investigations and algorithms, can multi-task, and can credibly interface between scientists, engineers and business stakeholders. Your expertise in synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication will enable you to answer specific business questions and innovate for the future.BASIC 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- 2+ 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 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 ...

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 ...

The Private Brands Discovery team designs innovative machine learning solutions to drive customer awareness for Amazon’s own brands and help customers discover products they love. Private Brands Discovery is an interdisciplinary team of Scientists and Engineers, who incubate and build disruptive solutions using cutting-edge technology to solve some of the toughest science problems at Amazon. To this end, the team employs methods from Natural Language Processing, Deep learning, multi-armed bandits and reinforcement learning, Bayesian Optimization, causal and statistical inference, and econometrics to drive discovery across the customer journey. Our solutions are crucial for the success of Amazon’s own brands and serve as a beacon for discovery solutions across Amazon.This is a high visibility opportunity for someone who wants to have business impact, dive deep into large-scale problems, enable measurable actions on the consumer economy, and work closely with scientists and engineers. As a scientist, you bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions.. With a focus on bias for action, this individual will be able to work equally well with Science, Engineering, Economics and business teams. Key job responsibilities- Drive applied science projects in machine learning end-to-end: from ideation over prototyping to launch. For example, starting from deep scientific thinking about new ways to support customers’ journeys through discovery, you analyze how customers discover, review and purchase Private Brands to innovate marketing and merchandising strategies. - Propose viable ideas to advance models and algorithms, with supporting argument, experiment, and eventually preliminary results. - Invent ways to overcome technical limitations and enable new forms of analyses to drive key technical and business decisions. - Present results, reports, and data insights to both technical and business leadership. - Constructively critique peer research and mentor junior scientists and engineers. - Innovate and contribute to Amazon’s science community and external research communities.BASIC QUALIFICATIONS- PhD, or Master's degree and 2+ years of CS, CE, ML or related field experience- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

We are seeking a talented and experienced Senior Data Engineer to join our Publisher Ad Server team within SupplyTech. In this role, you will be instrumental in designing, developing, and maintaining the data infrastructure that powers our advertising technology solutions for publishers. This role plays a crucial role in supporting data needs for science algorithms, budget allocation and contention, reporting, and generating actionable business insights.Key Responsibilities:• Architect and implement scalable data pipelines to process large volumes of advertising data in real-time• Develop and optimize ETL processes to integrate data from various sources into our data warehouse• Design and maintain data models to support reporting, analytics, forecasting, and machine learning initiatives• Collaborate with cross-functional teams, including software developers, applied scientists and business analysts, to understand requirements and translate them into technical solutions• Implement data quality checks and monitoring systems to ensure data accuracy and reliability• Optimize query performance and data storage solutions for improved efficiency• Support the development of business intelligence tools and dashboards for actionable insights• Contribute to forecasting models by providing clean, reliable data sets• Mentor junior engineers and contribute to the team's best practices and coding standardsRequirements:• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field• 5+ years of experience in data engineering, with a focus on big data technologies• Expertise in SQL and experience with big data processing frameworks (e.g., Apache Spark, Hadoop)• Proficiency in at least one programming language such as Python, Java, or Scala• Experience with cloud-based data solutions, preferably AWS services (e.g., Redshift, S3, EMR)• Strong understanding of data modeling, data warehousing, and ETL processes• Experience in supporting data science and forecasting projects• Familiarity with business intelligence tools (e.g., Tableau, PowerBI) is a plus• Knowledge of ad tech and digital advertising concepts is advantageous• Excellent problem-solving skills and attention to detail• Strong communication skills and ability to work in a collaborative environmentAt Amazon Ads, you'll have the opportunity to work on cutting-edge advertising technology that impacts millions of users and generates billions of impressions daily. Your work will directly contribute to data-driven decision making, scientific advancements, and business growth in the digital advertising space. Join our team and help shape the future of advertising technology through robust data engineering solutions!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- 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 ...

Amazon Worldwide Advertising is one of Amazon's fastest growing and most profitable businesses. Partner Experience and Growth (PEG) team leverages advanced analytics and experimentation to unlock value for our advertising partners and mutual customers i.e. the advertisers. The Science charter in PEG spearheads these efforts by optimizing the onboarding journey and providing data-driven insights to agencies and tool providers in the Amazon Ads ecosystem. Our proprietary tools provide granular visibility into what's working across audiences, creatives, targeting strategies, and more. These custom algorithmic recommendations uncover growth opportunities previously hidden in the data fog. Partners can confidently allocate budgets based on predicted performance, unlocking improved return on ad spend. And advertisers reap the benefits through expanded brand awareness, increased sales, and stronger customer loyalty over time.Key job responsibilitiesYou will participate in driving features from idea to deployment, and your work will directly impact millions of customers.You are going to love this job because you will:Map business requirements and customer needs to a scientific problem.Align the research direction to business requirements and make the right judgments on research/development schedule and prioritization.Research, design and implement scalable machine learning (ML), natural language, or supervised and unsupervised models to solve problems that matter to our customers in an iterative fashion.Mentor and develop junior scientists and developers who work on science problems in the same organization.Stay informed on the latest machine learning, natural language and/or artificial intelligence trends and make presentations to the larger engineering and science communities.Communicate complex technical concepts effectively to both technical and non-technical stakeholders, providing clear explanations on proposed solutions and their potential impact.About the teamThe Partner Science team’s vision is to drive the Advertising Partner flywheel by infusing science-based interventions at all stages of their journey with Amazon Ads including demand generation, partner selection, partner engagement, partner competition and innovation, ultimately improving the partner managed advertiser experience. We drive the vision by attracting and growing top scientist talents in an innovative, experimental, and collaborative culture. 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- Bachelor's degree- Experience with statistical models e.g. multinomial logistic regression ...

This Data Engineering position is responsible for supporting the data pipelines & engineering needs for Alexa analytics and Machine Learning (ML) products. This Data Engineer will build and optimize logical data model and data pipelines for large, complex, datasets across a variety of Alexa analytics product(s), as well as be accountable for ongoing data quality, efficiency, testing, and maintenance. The Data Engineer should thrive and have demonstrated success in an environment which offers ambiguously defined problems, big challenges, and quick changes. They will influence large-size data solutions/access to dataset(s) within our team's architecture, advising product managers, program managers, and other engineers on trade-offs and courses of action.We are looking for a passionate data engineer to optimize the consumption of these very large data sources we require to generate unique insights. As a data engineering leader within Alexa, we look to you for design, implementation, and successful delivery of large-scale, critical, or difficult data solutions involving a significant amount of work. You will share in the ownership of the technical vision and direction for advanced analytics and insight products. You will be a part of a team of top technical professionals developing complex systems at scale and with a focus on sustained operational excellence. Where needed, you integrate your team’s data solutions with those owned by other teams. You influence your team’s technical and business strategy by making insightful contributions to team priorities and overall data approach. You take the lead in identifying and solving ambiguous problems, architecture deficiencies, or areas where your team bottlenecks the innovations of other teams. We are looking for people who are motivated by thinking big, moving fast, and changing the way customers use data to drive profitability. If you love to implement solutions to hard problems while working hard, having fun, and making history, this may be the opportunity for you.The Data Engineer we are looking for:- Has knowledge of recent advances in distributed systems (e.g. MapReduce, MPP architectures, and NoSQL databases). You are proficient in a broad range of data design approaches and know when it is appropriate to use them (and when it is not).- Knowledge of engineering and operational excellence best practices. Can make enhancements that improve data processes (e.g., data auditing solutions, management of manually maintained tables, automating, ad-hoc or manual operation steps).- Works with engineers to develop efficient data querying and modeling infrastructure.- Understands how to make appropriate data trade-offs. Can balance customer requirements with technology requirements. Knows when to re-use code. Is judicious about introducing dependencies.- Writing code that a Data Engineer or Software Development Engineer unfamiliar with the system can understand.- Can create coherent Logical Data Models that drive physical design.- Delivers pragmatic solutions. You do things with the proper level of complexity the first time (or at least minimize incidental complexity).- Understands how to be efficient with resource usage (e.g., system hardware, data storage, query optimization, AWS infrastructure etc.)- Collaboration with colleagues from multidisciplinary science, engineering and business backgrounds.- Communicate proposals and results in a clear manner backed by data and coupled with actionable conclusions to drive business decisionsAbout the teamOur team owns a self-service analytics platform used by Alexa & AGI developers to identify trends in Alexa performance, assess customer impact, and troubleshoot failure patterns. Our customers include: scientists building and debugging ML models, analysts and researchers measuring the customer experience, developers troubleshooting defects and failures, and data teams building business reports and visualizing metrics.BASIC QUALIFICATIONS- 3+ years of data engineering experience- Experience with data modeling, warehousing and building ETL pipelines- Knowledge of distributed systems as it pertains to data storage and computing ...