Data Science

Are you inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Robotics. We are a smart team of doers who work passionately to apply cutting edge advances in robotics and software to solve real-world challenges that will transform our customers’ experiences. We invent new improvements every day. We are Amazon Robotics and we will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling, and fun.Amazon Robotics is seeking students to join us for a 5-6 month internship (full-time, 40 hours per week) as Data Science Co-op.Please note that by applying to this role you would be considered for Data Scientist spring co-op and fall co-op roles on various Amazon Robotics teams. The internship/co-op project(s) and location are determined by the team the student will be working on.Learn more about Amazon Robotics: https://amazon.jobs/en/teams/amazon-roboticsAbout the teamAmazon empowers a smarter, faster, more consistent customer experience through automation. Amazon Robotics automates fulfillment center operations using various methods of robotic technology including autonomous mobile robots, sophisticated control software, language perception, power management, computer vision, depth sensing, machine learning, object recognition, and semantic understanding of commands. Amazon Robotics has a dedicated focus on research and development to continuously explore new opportunities to extend its product lines into new areas.BASIC QUALIFICATIONS- Currently enrolled in a Master's or PhD program in Data Science, Mathematics, Statistics, Computer Science, Robotics, Engineering, Machine Learning, Computer Vision, Operations Research, Mathematics, Economics, Computer Science or a related quantitative field- Degree program must be based in the United States with an expected graduation of December 2025 or later- Must be eligible for and available for full-time (40 hours per week) internship based out of the assigned office location for the whole duration of the internship/co-op- At least 1 year of relevant academic research or industry experience within relevant science disciplines such as Machine Learning, Applied Statistics, Computer Vision, Optimization, or related- At least 1 year of experience working as a data scientist or a similar role involving data extraction, analysis, statistical modeling, and communication- At least 1 year of experience using data querying languages (e.g. SQL), scripting languages (e.g. Python), or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) ...

We are open to hiring candidates to work out of one of the following locations:New York, NY, USAAre you interested in playing a pivotal role in building innovative technology that protects Amazon’s customers?The Application Security Organization in Stores Security, builds solutions that keep Amazon systems and data secure on behalf of the Amazon customer. Our customers range from security engineers who need a comprehensive understanding of Amazon systems and their security state, to service teams who need solutions that make it easy to build and operate secure systems, to third party vendors who do business with Amazon. We use the latest technology to solve security problems at Amazon scale. We employ automation and machine learning to reduce, or eliminate, manual effort to help our internal customers raise the security bar. We have bold goals to stay ahead of the curve on security and delight our customers with great products.The Data Operations and Engineering team in the Application Security Organization is seeking a creative, curious, and ambitious Data Scientist to optimize the Amazon's application security monitoring systems, that collect data at scale, and use machine learning (ML) to detect adversarial action in our systems. You will play a key role in shaping the future of our security monitoring systems and analytics processes that vend security data at a massive scale across Amazon's systems.As a Data Scientist, you will complement our strengths and apply your data science skills, and tradecraft, to analyze terabytes of user behavior data, and systems data to detect threatening behaviors. You will build threat detection models and algorithms, which will be used to surface security anomalies, attacks and raise security investigations. You need to be highly motivated, eager to learn and be curious, and resourceful in finding novel ways to analyze data in order to produce actionable security insights.This is a highly visible role that requires partnering with multiple organizations, security leadership, and technology teams in order to extract the intelligence and effect change. You should have the experience and capability to create and present documentation to champion security causes. Excellent written and verbal communication skills are essential. You should be experienced in working with data to analyze and detect trends, outliers, and have advanced analytical, mathematical, and quantitative abilities.Key job responsibilities- Design and run experiments, research new algorithms, and find new ways to improve detection of fraudulent activities.- Research machine learning algorithms and implement by tailoring to business needs and test on large datasets.- Partner with scientists, engineers and product leaders to solve business and technology problems using scientific approaches to build new services that protect our customers.- Foster a culture of continuous engineering improvement through mentoring, feedback, and metrics.- Manipulating/mining data from databases- Providing analytical network support to improve quality and standard work results.- Translating business questions and concerns into specific quantitative questions that can be answered with available data using sound methodologies. In cases where questions cannot be answered with available data, work with engineers to produce the required data.- Retrieving, synthesizing, and presenting data in a format that is immediately useful to answering specific questions or improving system performance.- Applying statistical or machine learning knowledge to solve specific business problems.- Conducting written and verbal presentations to share insights and recommendations to audiences of varying levels of technical sophistication.About the teamAbout Amazon SecurityDiverse ExperiencesAmazon Security values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.Why Amazon Security?At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores.Inclusive Team CultureIn Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices.Training & 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, training, 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.BASIC QUALIFICATIONS- 2+ years of data scientist experience- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience- Experience applying theoretical models in an applied environment ...

Amazon's Optimal Inventory Health (OIH) org in Supply Chain Optimization (SCOT) group is looking for a Senior Data Scientist to build one of the most complex eCommerce systems in the world. The OIH drives long-term cash flow (LTFCF) growth by determining optimal inventory dispositions under uncertainties in demand, pricing, and supply across Amazon’s 21 marketplaces global network. OIH is in the unique position to drive the joint optimization across supply chain and marketing across the levers of Markdowns, Removals, Outlet, Deals, and Ads, etc. Our systems delivers hundreds of million dollar saving to Amazon each year. We are investing and building the next generation inventory disposition decision models based on large volume, high quality historical data using latest technologies like Reinforcement learning, Causal inference, Deep Learning Prediction, etc. As a part of our team, you will define the data science long-term vision and implementation to optimize across inventory disposition channels and deliver the best experience to Amazon customers through those levers across the whole product life cycle. You will have the opportunities to see your data insights directly impact million customers and generate large saving for Amazon.Key job responsibilitiesAs a Sr. Data Scientist at Amazon, you will connect with world leaders in your field working on similar problems. You will be working with massive-scale data and providing analytic leadership to scientists, product managers, engineers using these data. You will leverage your knowledge in machine learning, advanced analytics, metrics, reporting, and analytic tooling/languages to analyze and translate the data into meaningful insights. You will closely collaborate with business, scientists, and engineers. You will have end-to-end ownership of operational and technical aspects of the insights you are building for the business, and will play an integral role in strategic decision-making. Further, you will build solutions leveraging advanced analytics that enable stakeholders to manage the business and make effective decisions, partner with internal teams to identify process and system improvement opportunities.A day in the life- You will engage with Principal scientists and Senior scientists across organizations to shape the vision of the eCommerce decision systems across supply chain and marketing.- You will collaborate with talented product managers and software engineers to build the end to end systems.- You will work with stakeholders across retail, supply chain, finance etc. to understand the business operation process and bottlenecks and build solution to provide the best experience to Amazon customers through automated OIH actions.- You have the access to the richest eCommerce data and will be able to see the actual significant business impact quickly with the models you build.About the teamSupply Chain Optimization Technology (SCOT) is the core of the Amazon eCommerce business, which leverage science models and systems to automate the decisions and operations of the most complex supply chain in the world. Optimal Inventory Health (OIH) maximize the inventory value in Amazon through all the levers across traffic, marketing, pricing and reverse logistics.BASIC QUALIFICATIONS- 4+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience- 4+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or Bachelor's degree and 8+ years of professional or military experience- Experience in data applications using large scale distributed systems (e.g., EMR, Spark, Elasticsearch, Hadoop, Pig, and Hive) ...

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 ...

Are you passionate about automation, optimization, knowledge extraction, and artificial intelligence through the use of Machine Learning, Computer Vision, Optimization, Natural Language Processing, and Recommender systems? We have a team of experienced scientists with a critical business mission making revolutionary leaps forward in these spaces. On this team you will work with large multimodal datasets to build generative and discriminative models for optimizing large-scale manufacturing and fulfillment processes, analyze and model customer reading behavior to measure engagement and detect risks, and build AI-based systems for helping indie authors make their businesses successful. This will involve combining methods from several science domains with domain knowledge across multiple businesses into sophisticated ML workflows. Our team has mature areas and green-field opportunities. We offer scientific autonomy, value end-to-end ownership, and have a strong customer-focused culture.As a Research Scientist at Amazon, you will connect with world leaders in your field working on similar problems. You will be working with large distributed systems of data and providing technical leadership to the product managers, teams, and organizations building machine learning solutions. You will be tackling Machine Learning challenges in Supervised, Unsupervised, and Semi-supervised Learning; utilizing modern methods such as deep learning and classical methods from statistical learning theory, detection, estimation. Research Scientists are specialists with the deep expertise to drive the scientific vision for our products. They are externally aware of the state-of-the-art in their respective field of expertise and are constantly focused on advancing that state-of-the-art for improving Amazon’s products and services.Come join us as we revolutionize the book industry and deliver an amazing experience to our Kindle authors and readers.Key job responsibilitiesGreat candidates for this position will be experts in the areas of data science, machine learning, computer vision, optimization, NLP, or statistics. You will have hands-on experience with multiple science initiatives as well as be able to balance technical leadership with strong business judgment to make the right decisions about technology, models and methodological choices. You will strive for simplicity, and demonstrate significant creativity and high judgment.About the teamKindle Direct Publishing (KDP) and Print On Demand (POD) have empowered a new wave of self-motivated creators, tearing down barriers that once blocked writers from reaching readers. Our team builds rich applications and systems that empower anyone to realize their dream of becoming a published author. We strive to provide an experience that is powerful, yet simple to use and accessible to all. We focus on building systems that enable authors to design high quality digital and print books, reaching readers all around the world. This role will help ensure we maintain the trust of both our Authors and Readers by ensuring all books published to Amazon meet our standards.BASIC QUALIFICATIONS- PhD, or Master's degree and 4+ years of quantitative field research experience- Experience investigating the feasibility of applying scientific principles and concepts to business problems and products- Experience analyzing both experimental and observational data sets ...

Project Kuiper is an initiative to increase global broadband access through a constellation of 3,236 satellites in low Earth orbit (LEO). Its mission is to bring fast, affordable broadband to unserved and underserved communities around the world. Project Kuiper will help close the digital divide by delivering fast, affordable broadband to a wide range of customers, including consumers, businesses, government agencies, and other organizations operating in places without reliable connectivity.Kuiper's Commercial Revenue Operations (CRO) team is looking for a Senior Data Scientist to work hands on from concept to delivery on statistical analysis, prescriptive and predictive analysis, and machine learning implementation projects. We are looking for a problem solver with strong analytical skills and a solid understanding of statistics & Machine learning algorithm as well as a practical understanding of collecting, assembling, cleaning and setting up disparate data from enterprise systems to build models to help solve complex problems in the areas of sales forecasting, customer segmentation, what if simulations and demand forecasting.Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.Key job responsibilities• Develop ML models to measure long term impact of seller behaviors• Collaborate with product and engineering teams both within and outside of the CRO team to launch models and develop insights.• Use optimization, statistical, machine learning and analytical techniques to create scalable solutions for business problems.• Design, development and evaluation of highly innovative models for forecast, optimization and experimentation.• Research, experiment and implement novel approaches.• Work closely with other scientists in the team and across teams.• Work and collaborate effectively with product managers and software engineering teams to build algorithms and models and integrate successful models and algorithms in production systems.• Use the best practices in science: data integrity, design, test, and implementation and documentation.• Mentor and guide junior members in the team.• Contribute to Amazon's Intellectual Property through patents and internal and external publicationsAbout the teamKuiper Commercial Revenue Operations (CRO) is responsible for the business strategy, operations and systems for Kuiper's commercial business across multiple industry segments in multiple countries.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 ...

Amazon Web Services (AWS) is the world leader in providing a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers hundreds of thousands of businesses in 190 countries around the world! Passionate about building, owning and operating massively scalable systems? Want to make a billion-dollar impact? If so, we have an exciting opportunity for you. The AWS Managed Operations (MO) organization was founded in April 2023, with the objective to reduce operational load and toil through long-term engineering projects. MO is building the best-in-class engineering and operations team that will own the day-to-day operations for AWS Regions; improving the availability, reliability, latency, performance and efficiency to operate AWS regions. The AWS Managed Operations Data Science (MODS) Team is looking for a Data Scientist to lead the research and thought leadership to drive our data and insight strategy for AWS. You will be expected to serve as a Full Stack Data Scientist. You will be responsible for driving data-driven transformation across the organization. In this role, you will be responsible for the end-to-end data science lifecycle, from data exploration and feature engineering and ETL to model development. You will leverage a diverse set of tools and technologies, including SQL, Python, Spark, Hugging Face and various machine learning frameworks, to tackle complex business problems and uncover valuable insights.Your product analytics research will provide direction on the technology strategy of the Managed Operations organization. Your Decision Science artifacts will provide insights that inform AWS' Operations and Site Reliability Engineering teams. You will work on ambiguous and complex business and research science problems at scale. You are and comfortable working with cross-functional teams and systems.This position requires that the candidate selected be a U.S. citizen.10012Key job responsibilities- Collaboration & Cross Functional Relationships: Interact with business and software teams to understand their business requirements and operational processes- Data Exploration and Analysis: Conduct in-depth exploratory data analysis to understand the structure, quality, and patterns within complex datasets. Apply statistical and machine learning techniques to extract insights, identify trends, and uncover hidden relationships in the data. - Business Insights and Recommendations: Frame business problems into scalable solutions; translate complex data insights and model outputs into actionable recommendations that address the organization's strategic objectives.- Data Pipeline and Infrastructure: Contribute to the design and implementation of data pipelines, data lakes, and other data infrastructure components to support the organization's data-driven initiatives.- Metric Development and Monitoring: Define and develop advanced, customized metrics and key performance indicators (KPIs) that capture the nuances of the organization's strategic objectives and operational complexities. Continuously monitor and evaluate the performance of metrics - Prototype models by using high-level modeling languages such as R or in software languages such as Python. A software team will be working with you to transform prototypes into production.- Documentation & Continuous Improvement: Create, enhance, and maintain technical documentationA day in the lifeWhy AWSAmazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.Utility Computing (UC)AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (IoT), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.Inclusive Team CultureHere at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.Work/Life BalanceWe value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.Mentorship and Career GrowthWe’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.Diverse ExperiencesAmazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.About the teamThe MODS team is driven by a shared vision of achieving operational excellence through data analytics and machine learning. We provide actionable insights to allow our stakeholders to manage operational posture and operator experience and drive sustainable, safe, and efficient operations. We define, monitor, and predict metrics to provide recommendations on AWS operations that are diagnostic (why something happened), predictive (what will happen) and prescriptive (best course of action) in nature. We are a customer obsessed team driving lean operations in all of AWS through actionable insights and data strategies that drive process improvement. This position requires that the candidate selected be a U.S. citizen.BASIC QUALIFICATIONS- 3+ years of data scientist experience- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience- Knowledge of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.- Master's Degree in Statistics, Applied Math, Operations Research, Economics, or a related quantitative field with 2+ years' experience in Data Science or related Science discipline, OR, Bachelor's Degree in Statistics, Applied Math, Operations Research, Economics, or a related quantitative field with 5+ years' experience in Data Science or related Science discipline ...

Amazon Payments build systems that process payments at an unprecedented scale, with accuracy, speed, and mission-critical availability. We process millions of transactions every day worldwide across various payment methods. Over 100 million customers and merchants send hundreds of billions of dollars moving at light-speed through our systems annually. We are looking for a highly skilled, experienced, and motivated Applied Scientist to innovate and solve complex scientific optimization challenges at a massive scale. This Applied Scientist role will design and implement state-of-the-art AI optimization models that generate multi-billion dollar predictions of the highest level of visibility and importance for Amazon's Payments and Customer Experience. The scientist will work on implementing Agentic workflows within production systems that will tremendously improve developer productivity at scale. A successful candidate will be a problem solver who enjoys diving into data, is excited by difficult modeling challenges, and possesses strong communication skills to effectively interface between technical and business teams. You will contribute to the research community by working with other scientists across Amazon and our Payments Engineering as well as by collaborating with academic researchers and publishing papers. You will work closely with Software Development Engineers to invent and construct models on data at massive scale and it is likely that your work will end up in an Amazon product. Finally, you will also have exposure to senior leadership as we communicate results and provide scientific guidance to the business.Key job responsibilitiesAs a Applied Scientist you will: - Drive collaborative research and creative problem solving.- Write production-grade quality code for deploying machine learning and deep learning modes. - Constructively critique peer research and mentor junior scientists and engineers. - Create experiments and prototype implementations of state-of-the-art AI techniques.- Create agentic workflows using GenAI state-of-the-art techniques. - Collaborate with engineering teams to design and implement software solutions for science problems. - Contribute to progress of the Amazon and broader research communities by producing publication - Effectively collaborate in a fast paced environment with multiple teams in large organization (software development, Project Management, Build and Release, etc).About the teamAmazon Payments Machine Learning team leverages data across the payment lifecycle to build ML capabilities to improve payment-operations' success rates for verification, authentication, authorization, settlement, refund, disbursement etc. The team also leads impactful generative AI initiatives, driving reductions in operations, an improved developer experience, and friction-less client interactions.BASIC QUALIFICATIONS- PhD, or Master's degree and 6+ years of applied research experience- 3+ years of building machine learning models for business application experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

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 ...

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 ...

AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help. You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help.We are calling on engineers who wants to contribute to a sustainable future through technology. Join us in developing solutions for renewable energy portfolio and reduce carbon footprint of our materials in data centers. In 2019, Amazon co-founded The Climate Pledge and made a commitment to achieve net-zero carbon by 2040 —10 years ahead of the Paris Agreement. We invited others to join us and there are now more than 300 businesses and organizations across 51 industries and 29 countries that have signed the Pledge, which means we are collectively coming at the climate crisis from nearly every sector and nearly every angle.As part of our efforts to decarbonize our business, we became the world’s largest corporate purchaser of renewable energy in 2020, and last year, we reached 85% renewable energy across our business, and are on a path to power our operations with 100% renewable energy by 2025.We recently announced that AWS will be water positive by 2030, returning more water to communities than it uses in its direct operations. To learn more about AWS’s water+ commitment visit: Water Stewardship.Come join the team that is building the tools and innovative technology to manage our growing portfolio of renewable energy investments, including solar, on-shore and off-shore wind farms.Key job responsibilitiesOur Software Engineers develop a Sustainability Data Platform that hosts analytical and predictive models. This platform helps AWS teams gain business insights on sustainability. You will collaborate with Data Engineers to build large data models and Data Scientists to create predictive models, enhancing decision-making. You will work with internal and external AWS customers to build a system that measures and provides actionable decisions to reduce carbon footprint.A day in the lifeTo learn more, you can visit: amazon sustainability in the cloudAbout the teamWhy AWSAmazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.Diverse ExperiencesAmazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.Work/Life BalanceWe value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.Inclusive Team CultureHere at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.Mentorship and Career GrowthWe’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.BASIC QUALIFICATIONS- 3+ years of non-internship professional software development experience- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience- Experience programming with at least one software programming language ...

Are you interested in being a part of Amazon’s fastest growing business? Are you excited to work on latest Big Data technologies to help shape the future of Grocery data? If the answer to both these questions is Yes, then come be a part of Amazon Fresh’s Central Data Infrastructure team (DASH). Our vision is to build a world class, centralized and secure data infrastructure for Amazon’s Worldwide Omnichannel Grocery Business. Our mission is to make it extremely convenient for Internal stakeholders, 3P partners and the Grocery engineering community to access timely and accurate data for all their reporting and analytics needs. The scale and the complexity of the data we manage requires constant innovation and pushing the boundaries on what’s possible. This role offers you an opportunity to work on VP level visibility initiatives and make a lasting impression on how grocery data is managed and distributed across the globe.Key job responsibilitiesIn this role you will: - Help build the infrastructure to answer questions with data, using software engineering best practices, data management fundamentals, data storage principles, and recent advances in distributed systems - Manage AWS resources. - Collaborate with Business Intelligence Engineers to recognize and help adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation - Collaborate with Data Scientists to implement advanced analytics algorithms that exploit our rich data sets for statistical analysis, prediction, clustering and machine learning - Drive the architecture and technology choices that enable a world-class user experience - Develop expertise in a broad range of Amazon’s data resources and know when, how, and which to use and which not to use - Encourage the organization to adopt next-generation data architecture strategies, proposing both data flows and storage solutions - be comfortable with a degree of ambiguity and willing to develop quick proof of concepts, iterate and improve - Create extensible designs and easy to maintain solutions with the long term vision in mind - Have an understanding and empathy for business objectives, and continually align your work with those objectives and seek to deliver business value. You listen effectively.A day in the lifeSuccessful candidate would have extensive experience working with big data, building data warehouses and data processing services. They are effective at seeing data patterns and building generic data solutions to improve user experience. Proficiency in SQL and data modelling allows to create data warehouses and tables conforming to wide range of business needs. Previous ETL and MPP experience enables candidate to build extensible and scalable pipelines capable of processing large amounts of data in a short time, ex. >1T rows within few hours. Wide industry experience helps detect inefficiencies in existing designs and address them with minimal effort.About the teamF3 DASH is Amazon Fresh central data team responsible for the creation and maintenance of Amazon Grocery’s global data infrastructure. Our mission is to make all of grocery data easily accessible across multiple businesses by all users from a single location without any restrictions for all their reporting and analytics needs. Our long-term vision is to build a best-in-class data infrastructure to support worldwide grocery data to enable timely reporting and automated decision-making with standardized metrics to deliver top-line and bottom-line impact to Amazon’s grocery business.BASIC QUALIFICATIONS- 3+ years of data engineering experience- Experience with data modeling, warehousing and building ETL pipelines ...

Where will Amazon's growth come from in the next year? What about over the next five? Which product lines are poised to quintuple in size? Are we investing enough in our infrastructure, or too much? How do our customers react to changes in prices, product selection, or delivery times? These are among the most important questions at Amazon today. The Topline Forecasting team in the Supply Chain Optimization Technologies (SCOT) group is looking for innovative, passionate and results-oriented Data Scientists to answer these questions. You will have an opportunity to own the long-run outlook for Amazon’s global consumer business and shape strategic decisions at the highest level. The successful candidate will be able to formalize problem definitions from ambiguous requirements, build models using Amazon’s world-class data systems, and develop cutting-edge solutions for non-standard problems.Key job responsibilities- Develop new forecasting models or improve existing approaches using scalable techniques.- Extract data for analysis and model development from large, complex datasets to explain demand trends.- Closely work with engineering teams to build scalable, efficient systems that implement prototypes in production.- Distill problem definitions from informal business requirements and communicate technical solutions to senior business leaders.- Drive innovation and best practices in applied research across the Amazon research science community. BASIC QUALIFICATIONS- 2+ years of data scientist experience- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience- Experience applying theoretical models in an applied environment- Bachelor's degree ...

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

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 ROLEAs a Senior Applied Scientist, you will solve large complex real-world problems at scale, draw inspiration from the latest science and technology to empower undefined/untapped business use cases, delve into customer requirements, collaborate with tech and product teams on design, and create production-ready models that span various domains, including machine learning, artificial intelligence (AI), natural language processing (NLP), reinforcement learning (RL), real-time and distributed systems. Your primary focus will be on designing, developing, and deploying highly innovative modeling techniques to production to advance the state of the art in aforementioned domains. Your decision-making will consistently incorporate robust, data-driven business and technical judgment.ABOUT YOUYou have a background in modern programming languages, distributed system design, service-oriented architecture, and high scalability. Experience in advanced machine learning technologies and Artificial intelligence is a big plus. Equally important is the ability to multi-task, invent, create reliable and maintainable code, and find creative, scalable solutions to difficult problems. You'll work with experienced managers who'll care for you. We'll guide you on your career growth path and there's no shortage of technical challenges.As a Senior Applied Scientist, you will...- Understand large complex use cases across the business and design scalable, efficient, automated model solutions- Work closely with teams of scientists and software engineers to drive real-time model implementations and deliver novel and highly impactful features- Drive and lead strategic initiatives to employ the most recent advances in ML/AI in a fast-paced, experimental environment- Mentor and grow the scientists in the team and across Amazon ABOUT 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- 5+ years of industry experience in Deep learning, Natural Language Processing/Understanding, Reinforcement learning and Speech processing- PhD in one of the following disciplines: Computer Science, Machine Learning, Statistics, Data Science, Applied Math, Operational Research or a related quantitative field- 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 ...

Do you want a role with deep meaning and the ability to make a massive impact? Hiring top talent is not only critical to Amazon’s success—it can literally change the world. It took a lot of great hires to deliver innovations like AWS, Prime, and Alexa, which make life better for millions of customers around the world every day. As part of the Intelligent Talent Acquisition (ITA) team, you'll have the opportunity to reinvent the hiring process and deliver unprecedented scale, sophistication, and accuracy that Amazon's Talent Acquisition operations need.ITA is an industry-leading people science and technology organization made up of scientists, engineers, analysts, product professionals and more. Our shared goal is to fairly and precisely connect the right people to the right jobs. Last year, we delivered over 6 million online candidate assessments, replacing the "game of chance" with a merit-based approach that gives candidates the chance to showcase their true skills. Each year we help Amazon deliver billions of packages around the world by making it possible to hire hundreds of thousands of associates in the right quantity, at the right location and at exactly the right time. You’ll work on state-of-the-art research, advanced software tools, new AI systems, and machine learning algorithms to solve complex hiring challenges. Leveraging Amazon's in-house tech stack built on AWS, you'll have the autonomy and flexibility to bring innovative solutions to life. One day, we can bring these solutions to the rest of the world. Join ITA in using technologies to transform the hiring landscape and make a meaningful difference in people's lives. Together, we can solve the world's toughest hiring problems.Within ITA, the Candidate Generation team uses scientific experimentation, causal inference, generative AI, machine learning, and forecasting techniques to bring new and returning candidates to the top of the recruitment funnel. Driven by the goal of ensuring every marketing dollar is spent efficiently and effectively, the Candidate Generation team builds innovative decisioning products that provide tailored recommendations for recruiting challenges across a wide array of marketing channels globally. Our award-winning solutions tackle complex and ambiguous problems by applying science methodically and creatively, increasing candidate engagement while driving down costs. As a member of Candidate Generation, your work will modernize the field of Marketing and revolutionize the way we find and attract Amazonian talent.BASIC QUALIFICATIONS- 2+ years of data scientist experience- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience- Experience applying theoretical models in an applied environment ...

The 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 ...

Amazon co-ops are full-time positions, and co-op students should expect to work Monday-Friday, up to 40 hours per week typically between 8am-5pm. Specific team norms around working hours will be communicated by your manager. Students should not have conflicts such as classes or other employment during the Amazon work-day.Applicants must be currently enrolled in a co-op program at their school in the US, and should have a minimum of one quarter/semester/trimester remaining in their studies after their co-op concludes. By applying to this position, your application will be considered for all Data Engineer roles at all locations we hire for in the United States including but not limited to: Greater Seattle Area (Seattle, Bellevue, Redmond), Greater Bay Area (San Francisco, Sunnyvale, Santa Clara), Greater DMV (DC, MD, VA), Austin (TX), New York City (NY), Minneapolis (MN).You will be able to provide your preference of location and start date during the application process but, we cannot guarantee that we can meet your selection based on several factors including but not limited to the availability and business needs of this role. Finalization on the location and start dates available will be provided to you at the time of job offer. Start dates for our co-ops in this posting include the following period:Fall (Starts August/September 2025)Do you love building data pipelines? Are you excited by the opportunity to design tools and infrastructure needed to analyze large volumes of data? Do you want to help solve big data warehousing problems, and partner with stakeholders to understand how to best design and implement cutting edge data solutions that provide answers to key business questions? Do you want to be a part of a fast-paced environment and contribute to one of the most visited sites on the Internet?If this describes you, Amazon is looking for a Data Engineer Co-op to join one our many lines of business. Amazon co-ops have the opportunity to work alongside the industry’s brightest engineers who innovate every day on behalf of our customers. You will be matched to a manager and a mentor. You will have the opportunity to impact the evolution of Amazon technology as well as lead mission critical projects early in your career. Your work will contribute to solving some of the most complex technical challenges in the company.Key job responsibilitiesDuring a Data Engineer Co-op, you will/may:● Design, implement, and automate deployment of our distributed system for collecting and processing log events from multiple sources.● Design data schema and operate internal data warehouses and SQL/NoSQL database systems.● Own the design, development, and maintenance of ongoing metrics, reports, analyses, and dashboards that engineers, analysts, and data scientists use to drive key business decisions.● Monitor and troubleshoot operational or data issues in the data pipelines.● Drive architectural plans and implementation for future data storage, reporting, and analytic solutions.● Develop code based automated data pipelines able to process millions of data points.● Improve database and data warehouse performance by tuning inefficient queries.● Work collaboratively with Business Analysts, Data Scientists, and other internal partners to identify opportunities/problems.● Provide assistance to the team with troubleshooting, researching the root cause, and thoroughly resolving defects in the event of a problemA day in the lifeWe’re on the lookout for the curious, those who think big and want to define the world of tomorrow.At Amazon, you will grow into the high impact, visionary person you know you’re ready to be. Every day will be filled with exciting new challenges, developing new skills, and achieving personal growth.How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow.BASIC QUALIFICATIONS- Are enrolled in a co-op program at your university- Experience with database, data warehouse or data lake solutions- Experience with SQL- Experience with one or more scripting language (e.g., Python, KornShell)- Are 18 years of age or older- Experience with data transformation.- Currently working towards a Bachelor’s Degree in Computer Science, Computer Engineering, Data Science, Information Management, Information Systems, or other equivalent discipline, with an expected conferral date between March 2026 – December 2028. ...

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

At Audible, we believe stories have the power to transform lives. It’s why we work with some of the world’s leading creators to produce and share audio storytelling with our millions of global listeners. We are dreamers and inventors who come from a wide range of backgrounds and experiences to empower and inspire each other. Imagine your future with us.ABOUT THIS ROLEAudible's insights team leverages data to create value for our company and customers. We're seeking a Data Science Lead for our marketing and product measurement science team, to help us understand the return on investment (ROI) of our paid media and brand investments.As a Data Science Lead, you’ll manage a team of scientists working in the media measurement space. Your primary focus will be guiding scientific approach in developing and deploying advanced marketing measurement models (e.g., lifetime value, media mix). You will also lead Audible's scaled experimentation program, maintaining scientific integrity in global paid media experiments and guiding meta-analytical work to assess program health. Additionally, you will serve as the primary scientific contact for third-party media partners (Meta, Google), collaborating with them on new measurement approaches. You'll work with Audible marketers to translate sophisticated scientific methodologies into actionable business strategies, ultimately driving more effective marketing investments.ABOUT YOUAs a Data Science Lead, you will provide technical leadership in marketing measurement, design scalable model solutions, collaborate across scientific disciplines, communicate complex concepts clearly, and mentor team members to drive collective success.You have deep technical expertise across statistical modeling, machine learning, causal inference, and experimental design. You demonstrate a strong understanding of experimental design and evaluation. You are an expert in statistical modeling techniques. You have deep experience solving marketing-related problems, such as customer acquisition, retention, and ROI.You possess a strong ownership mindset and the ability to guide a technical team with minimal oversight. Your innovative problem-solving skills thrive in ambiguous environments, and you excel at translating complex scientific concepts into actionable insights. Outstanding business acumen, coupled with the ability to manage multiple projects simultaneously, defines your professional approach.You are committed to building a positive team culture, reliably delivering against commitments, and have a genuine passion for mentoring and developing scientific talent. You are adaptable across different scientific approaches and comfortable collaborating with cross-disciplinary scientific teams.As a Data Science Lead, you will...- Be a technical leader of other scientists, with substantial scope, impact, and visibility in the marketing measurement space- Understand complex use cases across the business and design scalable, efficient, automated model solutions, including developing, delivering, and improving various marketing measurement models- Collaborate with economists, applied scientists, and other data scientists on the right model specification(s) to serve business needs in the context of paid media measurement- Communicate clearly with senior audiences, translating complex scientific concepts into simplified, relevant outputs that can be quickly understood and actioned by both technical and non-technical colleagues- Mentor and grow scientists in your team and across AudibleABOUT AUDIBLEAudible is the leading producer and provider of audio storytelling. We spark listeners’ imaginations, offering immersive, cinematic experiences full of inspiration and insight to enrich our customers daily lives. We are a global company with an entrepreneurial spirit. We are dreamers and inventors who are passionate about the positive impact Audible can make for our customers and our neighbors. This spirit courses throughout Audible, supporting a culture of creativity and inclusion built on our People Principles and our mission to build more equitable communities in the cities we call home.BASIC QUALIFICATIONS- 3+ years managing a team of scientists or engineers, with a proven track record of hiring and developing junior team members- Master’s degree in relevant discipline and 5+ years of relevant professional experience (or equivalent)- Hands-on experience with marketing measurement models, including experience with articulating modeling trade-offs to business partners- Hands-on experience in designing and evaluating experiments, including experience with formal meta-analytical approaches for evaluating programs of experimentation- Hands-on experience with successfully putting marketing models into production- Fluency in Python and SQL- Experience influencing and delivering on a science roadmap ...