Data Science

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 RoleWe are looking for applied scientists to solve challenging and open-ended problems in the domain of user and content safety. As an applied scientist on Twitch's Community team, you will use machine learning to develop data products tackling problems such as harassment, spam, and illegal content. You will use a wide toolbox of ML tools to handle multiple types of data, including user behavior, metadata, and user generated content such as text and video. You will collaborate with a team of passionate scientists and engineers to develop these models and put them into production, where they can help Twitch's creators and viewers succeed and build communities.You will report to our Senior Applied Science Manager. This position is located in San Francisco, CA.You Will-Build machine learning products to protect Twitch and its users from abusive behavior such as harassment, spam, and violent or illegal content.-Work backwards from customer problems to develop the right solution for the job, whether a classical ML model or a state-of-the-art one.-Collaborate with Community Health's engineering and product management team to productionize your models into flexible data pipelines and ML-based services.-Continue to learn and experiment with new techniques in ML, software engineering, or safety so that we can better help communities on Twitch grow and stay safe.Perks- Medical, Dental, Vision & Disability Insurance- 401(k)- Maternity & Parental Leave- Flexible PTO- Amazon Employee DiscountBASIC QUALIFICATIONS- 2+ years of hands-on industry experience building models for NLP, deep learning, bot detection, anomaly detection or in another practical ML domain.- 2+ years experience writing high quality code to ship those models in production systems.- PhD / MSc Degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or similar quantitative field OR equivalent hands on experience.- Expertise with: Python and SQL, modern open source ML libraries (Pytorch, Tensorflow, etc.). Familiarity with operating in AWS or similar cloud-computing services. ...

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by preventing eCommerce fraud?Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems?Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you enjoy collaborating in a diverse team environment?If yes, then you may be a great fit to join the Amazon Buyer Risk Prevention (BRP) Machine Learning group. We are looking for a talented scientist who is passionate to build advanced algorithmic systems that help manage safety of millions of transactions every day.Key job responsibilitiesUse machine learning and statistical techniques to create scalable risk management systemsLearning and understanding large amounts of Amazon’s historical business data for specific instances of risk or broader risk trendsDesign, development and evaluation of highly innovative models for risk managementWorking closely with software engineering teams to drive real-time model implementations and new feature creationsWorking closely with operations staff to optimize risk management operations,Establishing scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementationTracking general business activity and providing clear, compelling management reporting on a regular basisResearch and implement novel machine learning and statistical approachesBASIC QUALIFICATIONS- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- 2+ years of building models for business application 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 ...

Amazon Devices team is looking for an experienced and motivated leader experienced with React Native. They will need to possesses a unique balance of technical depth and relationship management skills. Our partners develop apps and games for Amazon devices such as Fire tablets, Echo Show, Smart TVs (e.g. Fire TV Edition), streaming media players (e.g. Fire TV Stick) and Auto. As a Solutions Architect, you will work with top-tier partners to create incredible voice-enabled mobile experiences that will wow customers. You will act as the primary technical liaison between external partners and Amazon product teams to help shape their product roadmaps. Your role will be to guide partners as they productize and integrate with Amazon Services and enable them to grow their business through monetization and increase in engagement. You'll evangelize best practices through whitepapers, presentations and sample code. As you build relationships with your partners, you'll understand their business, product roadmap, and challenges. You'll use this information to advocate on their behalf to Amazon product teams, helping improve the feature sets and quality of Amazon products and services.If you have a passion for the app space, a solid understanding of the React, and a strong ability to communicate clearly and advocate for partner needs, this role is for you.Key job responsibilitiesProvide technical consultation to strategic app partnersCreate policies and establish processes for supporting app developersDevelop unique, compelling, and exciting presentations and demonstrations of new Amazon technologiesDeliver persuasive, passionate, high impact, high quality presentations to senior decision makersDocument best practices and create development resources that can be used by developersBuild reference architecture, frameworks and toolkits to drive adoption at scaleManage complex projects with significant impactBASIC QUALIFICATIONS- 2+ years of design, implementation, or consulting in applications and infrastructures experience- 4+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience ...

Recruiting the right candidates across all of Amazon is critical to our ability to innovate and build on behalf of our customers. The Data Engineer I role is an integral part of the team responsible for delivering accurate, secure, and timely recruiting data and metrics to our customers across Amazon.The ideal candidate is passionate about data and analytics, with a strong foundation in data engineering. They are eager to learn and grow, and thrive in a dynamic, fast-paced environment. The Data Engineer I will work closely with the wider team to architect, develop, and maintain scalable data infrastructure and data pipelines.Key job responsibilities- Design, implement, and support secure access to large datasets.- Architect, develop, and maintain scalable data infrastructure and data pipelines.- Extract, transform, and load data from a variety of sources using SQL, scripting, and AWS big data technologies.- Design and implement ETL pipelines and BI solutions.- Collaborate with business owners, developers, and BI Engineers to explore new data sources and deliver insights.- Stay up to date with advancements in big data technologies and contribute to pilot projects.- Proactively identify and resolve data-related issues, contributing to increased autonomy and productivity.BASIC QUALIFICATIONS- 1+ years of data engineering experience- Experience with data modeling, warehousing and building ETL pipelines- Experience with SQL- Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)- Experience with one or more scripting language (e.g., Python, KornShell) ...

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 ...

Alexa International Tech (AIT) team is looking for a passionate, talented, and inventive language data scientist to help build industry-leading technology with Large Language Models (LLMs) and multimodal systems, requiring strong deep learning and generative models knowledge.You will collaborate with fellow language data scientists, program managers, as well as stakeholders in science, engineering, and product teams to understand the role data plays in developing data sets and exemplars that meet customer needs. You will analyze and automate processes for collecting and annotating LLM inputs and outputs to assess data quality and measurement.You will apply state-of-the-art Generative AI techniques to analyze how well our data represents human language and run experiments to gauge downstream interactions. You will work collaboratively with other language data scientists and scientists to design and implement principled strategies for data optimization.Key job responsibilities- Collaborate with Scientists and Software Engineers to help design APIs and evaluate performance of LLM's- Produce and manipulate different types of language data, analyze, and provide efficient solutions- Design and lead a data collection; define scope and target, provide a guideline and training, guide teams cross sites to meet the quality bar, and run evaluation of data for hand off- Engineer prompts to guide generative AI to produce desired outputs in context- Automate operations and perform data analysis using Python or other scripting language- Advocate strict adherence to annotation guidelines- Test and deploy changes to Alexa's language understanding codebase- Identify and solve production issues that are impacting the Alexa customer experience,- Collaborate with other linguists, scientists and designers in creating optimal solutions to elevate the customer experience- Own the customer-facing machine learning and deterministic models for a specific domain of features- Use modeling tools to bootstrap and test new functionalitiesBASIC QUALIFICATIONS- 2+ years of data scientist experience- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience- Experience applying theoretical models in an applied environment ...

Amazon's WorldWide Grocery Stores Data & Analytics is seeking an experienced and proven Data Engineer (DE) to lead medium to large cross-functional strategic initiatives that support WWGS strategic goals. This is a unique opportunity for someone inspired by WWGS core values and is interested in Amazon’s high-growth grocery business to bring their whole self to the role.Key job responsibilitiesWe are seeking an experienced Sr. Data Engineer who will leverage their experience and talent to lead data integration, reporting, and analytics projects. This high impact role will be part of a team that will design and build our north star data infrastructure moving WWGDT away from our patchwork of 3p solutions. You will partner with other Data Engineers along with Software Developers, Business Intelligence Engineers, Analysts, Product Manager, and Program Managers inside and outside of the team to distill large, complicated datasets into automated, digestible analytic deliverables. You will use your organization skills, backbone, and high sense of ownership while collaborating with the rest of your team. You will have an opportunity to make a large impact on our modernized design, architecture, and development of data products. You will be a part of a data engineering team well versed in the legacy solutions and be asked to contribute to deliver on the future vision.A day in the lifeWork with your leadership to define and execute the data engineering strategy for WWGDT.Leverage SQL and coding skills (e.g., python, java, etc.) to extract, transform, and load data.Collaborate with internal and external teams to scope, design, build, and support data pipelines focusing on performance, cost, operational excellence, continuous improvement as well as delivering business value.Work within multiple technology stacks including working within custom built proprietary AWS framework to deliver data solutionsParticipate and lead standups and design sessions, maintain Jira health, and create artifactsLead and mentor your peersAbout the teamWe enable sophisticated, fact-based decision making across WWGS by delivering constantly evolving technology and analytic capabilities. This team will solve challenging and novel problems every day and have the opportunity to redefine the grocery industry while collaborating with multiple teams across WWGS and WholeFoods Market(WFM). You will be able to enjoy and contribute to the unique blend of Amazon and WFM Tech culture. You will be based out of Austin, TX, one of the best places to live and work. Most importantly, you’ll be contributing to WFM's Higher Purpose of Nourishing People and the Planet!BASIC QUALIFICATIONS- 3+ years of data engineering experience- Experience with data modeling, warehousing and building ETL pipelines ...

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 ...

Are you passionate about Generative AI (GenAI)? Do you want to help define the future of Go to Market (GTM) at AWS using generative AI? In this role, you will help some of our largest customers build and deploy GenAI enabled applications using Amazon SageMaker, fine tune and build Generative AI models, and help enterprise customers leverage these models to power end applications. You will engage with AWS product owners to influence product direction and help our customers tap into new markets by utilizing GenAI along with AWS Services.At Amazon, we’ve been investing deeply in artificial intelligence for over 20 years, and many of the capabilities customers experience in our products are driven by machine learning. Amazon.com’s recommendations engine is driven by machine learning (ML), as are the paths that optimize robotic picking routes in our fulfillment centers. Our supply chain, forecasting, and capacity planning are also informed by ML algorithms. Alexa is fueled by Natural Language Understanding and Automated Speech Recognition deep learning; as is Prime Air, and the computer vision technology in our new retail experience, Amazon Go. We have thousands of engineers at Amazon committed to machine learning and deep learning, and it’s a big part of our heritage.AWS is looking for a Generative AI Data Scientist, who will be the Subject Matter Expert (SME) for helping customers in designing solutions that leverage our Generative AI services. You will 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 for generative AI. As part of the Generative AI Worldwide Specialist organization, you will work closely with other Data Scientists and Machine Learning Architects from various geographies to enable large-scale customer use cases and drive the adoption of Amazon Web Services for GenAI services. You will interact with other Data Scientists and Solution Architects in the field, providing guidance on their customer engagements. You will develop white papers, blogs, reference implementations, and presentations to enable customers and partners to fully leverage Generative AI services on Amazon Web Services. You will also create field enablement materials for the broader technical field population, to help them understand how to integrate AWS Generative AI solutions into customer architectures. You drive effective feedback gathering from customers, and you distill and translate that feedback into clear business and technical requirements for product and engineering teams to review. You must have deep technical experience working with technologies related to large language models including LLM architectures, model evaluation, adapters, pre-training and fine-tuning techniques. You should be proficient with design, deployment, and evaluation of LLM-powered agents and tools and orchestration approaches. You must have experience with embedding model fine tuning and retrieval method evaluation approaches. Candidates must have great communication skills and be very technical, with the ability to impress Amazon Web Services customers at any level, from executive to developer. Previous experience with Amazon Web Services is desired but not required, provided you have experience building large scale solutions. You will get the opportunity to work directly with senior ML engineers and Data Scientists at customers, partners and Amazon Web Services service teams, influencing their roadmaps and driving innovation.Key job responsibilities- Customer Advisor- Implement, and deploy state of the art machine learning algorithms under Gen AI. You will build prototypes, PoCs, and explore new solutions. You will interact closely with our customers and with the academic community.- Thought Leadership – Evangelize AWS GenAI services and share best practices through forums such as AWS blogs, white-papers, reference architectures and public-speaking events such as AWS Summit, AWS re:Invent, etc. - Partner with Data Scientists, SAs, Sales, Business Development and the Generative AI Service teams to accelerate customer adoption and providing guidance on their customer engagements. - Act as a technical liaison between customers and the AWS Generative AI services teams to provide customer driven product improvement feedback. - Develop and support an AWS internal community of ML related subject matter experts worldwide. Create field enablement materials for the broader technical population, to help them understand how to integrate AWS GenAI solutions into customer architectures. About the teamWhy AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. 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- 5+ years of data scientist experience- Experience with statistical models e.g. multinomial logistic regression- 5+ years of experience with Python to analyze datasets, train , evaluate, deploy, and optimize models. ...

Amazon Web Services (AWS) is the world leader in providing a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers hundreds of thousands of businesses in 190 countries around the world!Passionate about building, owning and operating massively scalable systems? Want to make a billion-dollar impact? If so, we have an exciting opportunity for you.The AWS Managed Operations (MO) organization was founded in April 2023, with the objective to reduce operational load and toil through long-term engineering projects. MO is building the best-in-class engineering and operations team that will own the day-to-day operations for AWS Regions; improving the availability, reliability, latency, performance and efficiency to operate AWS regions.The AWS Managed Operations Data Science (MODS) Team is looking for a Senior Data Scientist to lead the research and thought leadership to drive our data and insight strategy for AWS. You will be expected to serve as a Full Stack Data Scientist. You will be responsible for driving data-driven transformation across the organization. In this role, you will be responsible for the end-to-end data science lifecycle, from data exploration and feature engineering and ETL to model development. You will leverage a diverse set of tools and technologies, including SQL, Python, Spark, Hugging Face and various machine learning frameworks, to tackle complex business problems and uncover valuable insights.Your product analytics research will provide direction on the technology strategy of the Managed Operations organization. Your Decision Science artifacts will provide insights that inform AWS' Operations and Site Reliability Engineering teams. You will work on ambiguous and complex business and research science problems at scale. You are and comfortable working with cross-functional teams and systems.Arlington, VA (HQ2)This role will sit in our new headquarters in Northern Virginia, where Amazon will invest $2.5 billion dollars, occupy 4 million square feet of energy efficient office space, and create at least 25,000 new full-time jobs. Our employees and the neighboring community will also benefit from the associated investments from the Commonwealth including infrastructure updates, public transportation improvements, and new access to Reagan National Airport.By working together on behalf of our customers, we are building the future one innovative product, service, and idea at a time. Are you ready to embrace the challenge? Come build the future with us.This position requires that the candidate selected be a U.S. citizen.10012Key job responsibilities- Collaboration & Cross Functional Relationships: Interact with business and software teams to understand their business requirements and operational processes- Data Exploration and Analysis: Conduct in-depth exploratory data analysis to understand the structure, quality, and patterns within complex datasets. Apply statistical and machine learning techniques to extract insights, identify trends, and uncover hidden relationships in the data.- Business Insights and Recommendations: Frame business problems into scalable solutions; translate complex data insights and model outputs into actionable recommendations that address the organization's strategic objectives.- Data Pipeline and Infrastructure: Contribute to the design and implementation of data pipelines, data lakes, and other data infrastructure components to support the organization's data-driven initiatives.- Metric Development and Monitoring: Define and develop advanced, customized metrics and key performance indicators (KPIs) that capture the nuances of the organization's strategic objectives and operational complexities. Continuously monitor and evaluate the performance of metrics- Prototype models by using high-level modeling languages such as R or in software languages such as Python. A software team will be working with you to transform prototypes into production.- Documentation & Continuous Improvement: Create, enhance, and maintain technical documentationA day in the lifeWhy AWSAmazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.Utility Computing (UC)AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (IoT), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.Inclusive Team CultureHere at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.Work/Life BalanceWe value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.Mentorship and Career GrowthWe’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.Diverse ExperiencesAmazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.About the teamThe MODS team is driven by a shared vision of achieving operational excellence through data analytics and machine learning. We provide actionable insights to allow our stakeholders to manage operational posture and operator experience and drive sustainable, safe, and efficient operations.We define, monitor, and predict metrics to provide recommendations on AWS operations that are diagnostic (why something happened), predictive (what will happen) and prescriptive (best course of action) in nature.We are a customer obsessed team driving lean operations in all of AWS through actionable insights and data strategies that drive process improvement.About the teamThe MODS team is driven by a shared vision of achieving operational excellence through data analytics and machine learning. We provide actionable insights to allow our stakeholders to manage operational posture and operator experience and drive sustainable, safe, and efficient operations.We define, monitor, and predict metrics to provide recommendations on AWS operations that are diagnostic (why something happened), predictive (what will happen) and prescriptive (best course of action) in nature.We are a customer obsessed team driving lean operations in all of AWS through actionable insights and data strategies that drive process improvement.BASIC QUALIFICATIONS- 6+ 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 ...

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 ...

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 ...

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

AWS Elastic Compute Cloud (EC2) Capacity Org is looking for an experienced applied optimization expert. This leader will join the Optimization Science Team to design, implement, and scale decision-making algorithms to manage EC2’s virtual and physical capacity systems.EC2 Capacity owns EC2’s top-level customer satisfaction metric capacity availability and the forecasting & decision-making systems which drive significant capex investments in server ordering for AWS data centers. Optimization Science is a core team involved in the end-to-end design and implementation of various decision-making systems, which manage the trade-off between capex and capacity availability while matching demand and supply at different planning horizons. The stakeholders and partners include engineering and product management orgs within EC2 as well as the AWS Infrastructure Supply Chain (AIS) organization.We are seeking an expert with a strong background in mathematical optimization with excellent modeling skills, and expertise in the numerical solution of continuous and discrete problems using exact and and heuristic methods applied to very large-scale problems. Experience with decision-making under uncertainty; e.g., robust or stochastic optimization is an advantage. The candidate will apply their knowledge to match the end-customer demand for virtual machines to physical resource supply at horizons ranging from five minutes to 13 years. The variety of problems requires principled mathematical decomposition and a good interface design between inputs and outputs at various horizons. Navigating the ambiguity of design choices across horizons is a critical component of the role. In a typical project, we analyze large volumes of data, and then develop a prescriptive optimization model with inputs from ML or statistical models and business users. Our solution approaches are validated through simulations and / or production A/B tests. Being successful requires having the scientific breadth to understand the interactions between different phases of a project from data analysis through to production, including resolving issues after rollout.As a Senior Applied Scientist on the EC2 Optimization Science team, you are critical to the speed and excellence of the end-to-end deliveries of production systems with optimization-based analytical engines. You will be hands-on with the mathematical modeling and implementation, and will also contribute to the design of the engineering system with the scalability, extensibility, maintainability, and correctness of the optimization engine in mind. You will review approaches by other scientists and engineers in terms of business relevance, technical validity, engineering / science interface, and computational performance. You will mentor and lead junior scientists by example. Communicating your results to guide the direction of the business and working with software development teams to implement your ideas in code is key to success. You will write technical, and less frequently, business documents that influence engineering investments and business direction. Collaborating with other scientists, software engineers, and product managers, you will develop creative, novel, and data-driven approaches to improve our existing cloud compute offerings and define new ones in a fast-paced and quickly changing environment, improving the experience of our customers and impacting the bottom line of EC2.**Basic Qualifications**- PhD in Operations Research, Applied Mathematics, Computer Science, Statistics, or a related field. A PhD can be replaced by a master's degree in the same fields and four years of relevant academic and / or industry research experience.- At least 3 years of academic and / or industry experience after the PhD degree in solving large-scale optimization problems.- Track record of delivering analytical solutions with business impact.- In-depth knowledge of exact, approximation algorithms, and heuristic methods for solving difficult optimization problems like resource allocation, vehicle routing, network design.- In-depth knowledge of continuous and discrete optimization methods accompanied by associated expertise in the use of tools and the latest technology (e.g. CPLEX, Gurobi, XPRESS).- Ability to implement models and tools through the use of high-level modeling languages (e.g., AMPL, Mosel, R, Matlab).- Experience in prototyping and developing software in traditional programming languages (e.g., C++, Java, Python, Julia) using mathematical solver interfaces.- Familiarity with SQL and experience with very large-scale data. The ability to manipulate data by writing scripts (Python, Perl, Ruby) is a plus.- Good writing skills to document the models and analyses and for presenting business cases with results/conclusions in order to influence important decisions.**Preferred Qualifications**These are not required, but are a plus:- Knowledge and experience in statistical analysis and machine learning.- Publications in refereed academic journals.- Previous work in cloud computing.BASIC QUALIFICATIONS- PhD in operations research, applied mathematics, theoretical computer science, or equivalent, or Master's degree and 7+ years of building machine learning models or developing algorithms for business application experience ...

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 ...

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

Amazon is continuing to invest in its Advertising business to tap into the growing online advertising market. The Publisher Technologies team builds and operates extensible services that empower 1P Publishers to improve the monetization of their customer experiences, along with the experiences themselves. We bias toward standards-based and flexible designs that allow Publishers the ability to invent on top of our solutions and to interoperate well with other advertising technology providers; both internal and external.The Publisher Technology Data, Insights, and Analytics team enables faster data-driven decision making for Publishers and Monetization teams by providing them with near real time data, data management tools, actionable insights, and an easy-to-use reporting experience. Our data products provide Publishers and Monetization teams with the capabilities necessary to better understand the performance of their Advertising products along with supporting machine learning at scale.In this role, you will join a team whose data products and services empower hundreds of teams across Amazon with near real time data to support big data analytics, insights, and machine learning at scale. You will collaborate with cross-functional teams to design, develop, and implement advanced data tools, predictive models, and machine learning algorithms to support Advertising strategies and optimize revenue streams. You will analyze large-scale data to identify patterns and trends, and design and run A/B experiments to improve Publisher and advertiser experiences. Key job responsibilities- Design and lead large projects and experiments from beginning to end, and drive solutions to complex or ambiguous problems- Create tools and solve challenges using statistical modeling, machine learning, optimization, and/or other approaches for quantifiable impact on the business- Use broad expertise to recommend the right strategies, methodologies, and best practices, teaching and mentoring others- Key influencer of your team’s business strategy and of related teams’ strategies- Communication and documentation of methodologies, insights, and recommendations for senior leaders with various levels of technical knowledgeBASIC 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- Prior experience in advertising or digital marketing, with an understanding of programmatic advertising and the digital advertising ecosystem ...

The vision for Alexa is to be the world’s best personal assistant. Such an assistant will play a vital role in managing the communication lives of customers, from drafting communications to coordinating with people on behalf of customers. At Alexa Communications, we’re leveraging Generative AI to bring this vision to life.If you’re passionate about building magical experiences for customers, while solving hard, complex technical problems, then this role is for you. You will operate at the intersection of large language models, real time communications, voice and graphical user interfaces, and mixed reality to deliver cutting-edge features for end users.Come join us to invent the future of how millions of customers will communicate with and through their virtual AI assistants.Key job responsibilitiesThe Comms Experience Insights (CXI) team is looking for an experienced, self-driven, analytical, and strategic Data Scientist II. We are looking for an individual who is passionate about tying together huge amounts of data to answer complex stakeholder questions. You should have deep expertise in translating data into meaningful insights through collaboration with Data Engineers and Business Analysts. You should also have extensive experience in model fitting and explaining how the insights derived from those models impact a business. In this role, you will take data curated by a dedicated team of Data Engineers to conduct deep statistical analysis on usage trends.The right candidate will possess excellent business and communication skills, be able to work with business owners to develop and define key business questions, and be able to collaborate with Data Engineers and Business Analysts to analyze data that will answer those questions. The right candidate should have a solid understanding of how to curate the right datasets that can be used to train data models, and the desire to learn and implement new technologies and services to further a scalable, self-service model.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 ...

Amazon Devices is one of the most innovative and fastest growing businesses at Amazon. Within the Amazon Devices, the Pre-Owned business team owns the Trade-in experience, and manages the sales of a broad portfolio of pre-owned devices. We set big goals and are looking for people who can help us reach and exceed them.Do you want to work in a role where you are encouraged to build and have the autonomy to push boundaries? Do you love to see an immediate impact from your actions? The Devices team at Amazon is seeking a talented and experienced Segmentation Scientist to drive our new initiative, which aims to create a best-in-class trade-in and upgrade experience for Amazon Device customers. In this role, you will leverage science skills to plan and execute experiments, identify key customer segments, analyze results, and predict benefits. You'll work cross-functionally with product, marketing, and analytics teams to develop scientific targeting strategies to effectively reach various customer segments with personalized offers. You'll apply advanced data science techniques to solve complex business problems and directly impact the customer experience. Your work will help millions of customers access the latest innovations while driving business value. The ideal candidate will have strong analytical and communication skills, experience with experimental design and customer segmentation, and the ability to translate data into actionable insights. If you're passionate about using data to drive product strategy and customer experience, we'd love to talk to you about joining our team!Key job responsibilities- Design and plan upgrade experiments across product lines, customer segments, and multiple channels (e.g., email, gateway, on-device amongst other channels)- Develop customer segmentation models to identify high-value upgrade targets- Develop Propensity Models based on the experimentation- Analyze experiment results and customer behavior to uncover key insights- Build predictive models to forecast upgrade rates and program benefits- Partner with marketing teams to test, evaluate, and refine targeted messaging and optimal channel mix for different customer segments, with the goal of optimizing channel strategy, engagement, and conversion rates - Collaborate with product teams to refine the upgrade experience based on data insights - Present findings and recommendations to leadership to drive strategy This is an exciting opportunity to shape a major strategic initiative for Amazon Devices. 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- Bachelor's degree, or 5+ years of professional or military experience- Experience working with complex data sets- Experience communicating results to senior leadership ...

AEE Science and AI team is focused on advancing customer experience on 1) Expansions: building the end-to-end Day0 search relevance models (ranking and matching) for new Amazon marketplaces, 2) Exports: improving the search relevance for cross-border (exports) customers, and 3) Emerging Markets Retail Efficiency related initiatives. We focus on algorithms and machine learning model developments, and optimize for recall (completeness) and precision (accuracy), measured through Spare Result Rate (SRR) and Irrelevant Result Rate (IRR) respectively. We are also leveraging Generative AI and LLMs to improve retail operations and reduce cost-to-serve.In this role, you will leverage your expertise in machine learning, information retrieval, and natural language processing to design, implement, and optimize ranking and matching algorithms that improve user experience and satisfaction. Key responsibilities include analyzing large datasets to identify patterns and insights, developing and fine-tuning models to improve search result relevance, and collaborating with cross-functional teams to integrate these models into our search systems. You will conduct experiments to evaluate model performance, utilizing A/B testing and other methodologies to ensure continuous improvement.The ideal candidate will possess a strong background in applied mathematics, computer science, or a related field, with experience in search technologies and a passion for solving complex problems. You will have the opportunity to make a significant impact on our product by driving advancements in search relevance that directly enhance user engagement and outcomes.Key job responsibilities1. Model Development: Design, implement, and refine machine learning models for ranking and matching to enhance search relevance and user satisfaction.2. Data Analysis: Analyze large datasets to extract insights, identify trends, and inform model improvements, ensuring data-driven decision-making.3. Algorithm Optimization: Continuously evaluate and optimize existing algorithms to improve search accuracy and performance through experimentation and iteration.4. Performance Evaluation: Conduct A/B testing and other evaluation methodologies to assess model effectiveness, drawing actionable conclusions to guide further development.5. Cross-Functional Collaboration: Work closely with product managers, engineers, and UX researchers to integrate search models into production systems and align with overall product goals.6. Research and Innovation: Stay current with advancements in machine learning, natural language processing, and information retrieval to drive innovation in search technologies.7. Reporting: Document methodologies, findings, and model performance metrics, and communicate results effectively to stakeholders at all levels.BASIC QUALIFICATIONS- Experience programming in Java, C++, Python or related language- PhD in computer science, machine learning, engineering, or related fields ...