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| data scientist mckinsey salary: Data-Driven Innovation Big Data for Growth and Well-Being OECD, 2015-10-06 This report improves the evidence base on the role of Data Driven Innovation for promoting growth and well-being, and provide policy guidance on how to maximise the benefits of DDI and mitigate the associated economic and societal risks. |
| data scientist mckinsey salary: Getting Started with Data Science Murtaza Haider, 2015-12-14 Master Data Analytics Hands-On by Solving Fascinating Problems You’ll Actually Enjoy! Harvard Business Review recently called data science “The Sexiest Job of the 21st Century.” It’s not just sexy: For millions of managers, analysts, and students who need to solve real business problems, it’s indispensable. Unfortunately, there’s been nothing easy about learning data science–until now. Getting Started with Data Science takes its inspiration from worldwide best-sellers like Freakonomics and Malcolm Gladwell’s Outliers: It teaches through a powerful narrative packed with unforgettable stories. Murtaza Haider offers informative, jargon-free coverage of basic theory and technique, backed with plenty of vivid examples and hands-on practice opportunities. Everything’s software and platform agnostic, so you can learn data science whether you work with R, Stata, SPSS, or SAS. Best of all, Haider teaches a crucial skillset most data science books ignore: how to tell powerful stories using graphics and tables. Every chapter is built around real research challenges, so you’ll always know why you’re doing what you’re doing. You’ll master data science by answering fascinating questions, such as: • Are religious individuals more or less likely to have extramarital affairs? • Do attractive professors get better teaching evaluations? • Does the higher price of cigarettes deter smoking? • What determines housing prices more: lot size or the number of bedrooms? • How do teenagers and older people differ in the way they use social media? • Who is more likely to use online dating services? • Why do some purchase iPhones and others Blackberry devices? • Does the presence of children influence a family’s spending on alcohol? For each problem, you’ll walk through defining your question and the answers you’ll need; exploring how others have approached similar challenges; selecting your data and methods; generating your statistics; organizing your report; and telling your story. Throughout, the focus is squarely on what matters most: transforming data into insights that are clear, accurate, and can be acted upon. |
| data scientist mckinsey salary: The Data Science Design Manual Steven S. Skiena, 2017-07-01 This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains “War Stories,” offering perspectives on how data science applies in the real world Includes “Homework Problems,” providing a wide range of exercises and projects for self-study Provides a complete set of lecture slides and online video lectures at www.data-manual.com Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter Recommends exciting “Kaggle Challenges” from the online platform Kaggle Highlights “False Starts,” revealing the subtle reasons why certain approaches fail Offers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com) |
| data scientist mckinsey salary: The Big Unlock Paddy Padmanabhan, 2017-11-17 Along with a shift towards value-based care, a digital transformation is under way in health care. However, health care enterprises are having a hard time keeping up with advances in information technology. Organizations that could once spend months or years developing a strategy to deliver solutions now must implement changes on a near real-time basis. Complicating matters is the emergence of new data sources, new technology architectures and models, and new methods to analyze an avalanche of data. This book provides a framework for understanding the competitive landscape for digital health and advanced analytics solutions that are harnessing data to unlock insights. It reveals a set of key principles, or universal themes, for success in the digital health marketplace. Whether youre a health care information technology specialist, a digital health startup or technology firm with a strategic focus on health care, a venture capitalist, or just interested in the industry structure and the emerging technology landscape in health care, youll learn how to grow revenue and profits while creating a sustainable competitive advantage. Take a key step in navigating the exciting transformation of health care, and harness the power of data and analytics with The Big Unlock. |
| data scientist mckinsey salary: Getting a Big Data Job For Dummies Jason Williamson, 2014-12-10 Hone your analytic talents and become part of the next big thing Getting a Big Data Job For Dummies is the ultimate guide to landing a position in one of the fastest-growing fields in the modern economy. Learn exactly what big data means, why it's so important across all industries, and how you can obtain one of the most sought-after skill sets of the decade. This book walks you through the process of identifying your ideal big data job, shaping the perfect resume, and nailing the interview, all in one easy-to-read guide. Companies from all industries, including finance, technology, medicine, and defense, are harnessing massive amounts of data to reap a competitive advantage. The demand for big data professionals is growing every year, and experts forecast an estimated 1.9 million additional U.S. jobs in big data by 2015. Whether your niche is developing the technology, handling the data, or analyzing the results, turning your attention to a career in big data can lead to a more secure, more lucrative career path. Getting a Big Data Job For Dummies provides an overview of the big data career arc, and then shows you how to get your foot in the door with topics like: The education you need to succeed The range of big data career path options An overview of major big data employers A plan to develop your job-landing strategy Your analytic inclinations may be your ticket to long-lasting success. In a highly competitive job market, developing your data skills can create a situation where you pick your employer rather than the other way around. If you're ready to get in on the ground floor of the next big thing, Getting a Big Data Job For Dummies will teach you everything you need to know to get started today. |
| data scientist mckinsey salary: The Data Industry Chunlei Tang, 2016-05-03 Provides an introduction of the data industry to the field of economics This book bridges the gap between economics and data science to help data scientists understand the economics of big data, and enable economists to analyze the data industry. It begins by explaining data resources and introduces the data asset. This book defines a data industry chain, enumerates data enterprises’ business models versus operating models, and proposes a mode of industrial development for the data industry. The author describes five types of enterprise agglomerations, and multiple industrial cluster effects. A discussion on the establishment and development of data industry related laws and regulations is provided. In addition, this book discusses several scenarios on how to convert data driving forces into productivity that can then serve society. This book is designed to serve as a reference and training guide for ata scientists, data-oriented managers and executives, entrepreneurs, scholars, and government employees. Defines and develops the concept of a “Data Industry,” and explains the economics of data to data scientists and statisticians Includes numerous case studies and examples from a variety of industries and disciplines Serves as a useful guide for practitioners and entrepreneurs in the business of data technology The Data Industry: The Business and Economics of Information and Big Data is a resource for practitioners in the data science industry, government, and students in economics, business, and statistics. CHUNLEI TANG, Ph.D., is a research fellow at Harvard University. She is the co-founder of Fudan’s Institute for Data Industry and proposed the concept of the “data industry”. She received a Ph.D. in Computer and Software Theory in 2012 and a Master of Software Engineering in 2006 from Fudan University, Shanghai, China. |
| data scientist mckinsey salary: Analytics and Knowledge Management Suliman Hawamdeh, Hsia-Ching Chang, 2018-08-06 The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics technique. Analytics and Knowledge Management examines the role of analytics in knowledge management and the integration of big data theories, methods, and techniques into an organizational knowledge management framework. Its chapters written by researchers and professionals provide insight into theories, models, techniques, and applications with case studies examining the use of analytics in organizations. The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics techniques. Analytics, on the other hand, is the examination, interpretation, and discovery of meaningful patterns, trends, and knowledge from data and textual information. It provides the basis for knowledge discovery and completes the cycle in which knowledge management and knowledge utilization happen. Organizations should develop knowledge focuses on data quality, application domain, selecting analytics techniques, and on how to take actions based on patterns and insights derived from analytics. Case studies in the book explore how to perform analytics on social networking and user-based data to develop knowledge. One case explores analyze data from Twitter feeds. Another examines the analysis of data obtained through user feedback. One chapter introduces the definitions and processes of social media analytics from different perspectives as well as focuses on techniques and tools used for social media analytics. Data visualization has a critical role in the advancement of modern data analytics, particularly in the field of business intelligence and analytics. It can guide managers in understanding market trends and customer purchasing patterns over time. The book illustrates various data visualization tools that can support answering different types of business questions to improve profits and customer relationships. This insightful reference concludes with a chapter on the critical issue of cybersecurity. It examines the process of collecting and organizing data as well as reviewing various tools for text analysis and data analytics and discusses dealing with collections of large datasets and a great deal of diverse data types from legacy system to social networks platforms. |
| data scientist mckinsey salary: Health Informatics Sixth Edition Supplement: Practical Guide for Healthcare and Information Technology Professionals Ann K. Yoshihashi, Robert E. Hoyt, 2016-11-15 Health Informatics: Practical Guide for Health and Information Technology Professionals Sixth Edition Supplement adds 3 new chapters. The supplement has learning objectives, case studies, recommended reading, future trends, key points, and references. Introduction to Data Science, provides a comprehensive overview with topics including databases, machine learning, big data and predictive analytics. Clinical Decision Support (CDS), covers current and salient aspects of CDS functionality, implementation, benefits, challenges and lessons learned. International Health Informatics, highlights the informatics initiatives of developed and developing countries on each continent. Available as a paperback and eBook. For more information about the textbook, visit www.informaticseducation.org. For instructors, an Instructor Manual, PDF version and PowerPoint slides are available under the Instructor's tab. |
| data scientist mckinsey salary: It's All Analytics! Scott Burk, Gary D. Miner, 2020-05-25 It's All Analytics! The Foundations of AI, Big Data and Data Science Landscape for Professionals in Healthcare, Business, and Government (978-0-367-35968-3, 325690) Professionals are challenged each day by a changing landscape of technology and terminology. In recent history, especially in the last 25 years, there has been an explosion of terms and methods that automate and improve decision-making and operations. One term, analytics, is an overarching description of a compilation of methodologies. But AI (artificial intelligence), statistics, decision science, and optimization, which have been around for decades, have resurged. Also, things like business intelligence, online analytical processing (OLAP) and many, many more have been born or reborn. How is someone to make sense of all this methodology and terminology? This book, the first in a series of three, provides a look at the foundations of artificial intelligence and analytics and why readers need an unbiased understanding of the subject. The authors include the basics such as algorithms, mental concepts, models, and paradigms in addition to the benefits of machine learning. The book also includes a chapter on data and the various forms of data. The authors wrap up this book with a look at the next frontiers such as applications and designing your environment for success, which segue into the topics of the next two books in the series. |
| data scientist mckinsey salary: Operating AI Ulrika Jagare, 2022-04-19 A holistic and real-world approach to operationalizing artificial intelligence in your company In Operating AI, Director of Technology and Architecture at Ericsson AB, Ulrika Jägare, delivers an eye-opening new discussion of how to introduce your organization to artificial intelligence by balancing data engineering, model development, and AI operations. You'll learn the importance of embracing an AI operational mindset to successfully operate AI and lead AI initiatives through the entire lifecycle, including key areas such as; data mesh, data fabric, aspects of security, data privacy, data rights and IPR related to data and AI models. In the book, you’ll also discover: How to reduce the risk of entering bias in our artificial intelligence solutions and how to approach explainable AI (XAI) The importance of efficient and reproduceable data pipelines, including how to manage your company's data An operational perspective on the development of AI models using the MLOps (Machine Learning Operations) approach, including how to deploy, run and monitor models and ML pipelines in production using CI/CD/CT techniques, that generates value in the real world Key competences and toolsets in AI development, deployment and operations What to consider when operating different types of AI business models With a strong emphasis on deployment and operations of trustworthy and reliable AI solutions that operate well in the real world—and not just the lab—Operating AI is a must-read for business leaders looking for ways to operationalize an AI business model that actually makes money, from the concept phase to running in a live production environment. |
| data scientist mckinsey salary: Health Informatics: Practical Guide Seventh Edition William R. Hersh, Robert E. Hoyt, 2018 Health informatics is the discipline concerned with the management of healthcare data and information through the application of computers and other information technologies. The field focuses more on identifying and applying information in the healthcare field and less on the technology involved. Our goal is to stimulate and educate healthcare and IT professionals and students about the key topics in this rapidly changing field. This seventh edition reflects the current knowledge in the topics listed below and provides learning objectives, key points, case studies and extensive references. Available as a paperback and eBook. Visit the textbook companion website at http://informaticseducation.org for more information.--Page 4 de la couverture. |
| data scientist mckinsey salary: Quality Experience Telemetry Alka Jarvis, Luis Morales, Johnson Jose, 2018-04-03 Telemetry is an automated way of collecting data at remote sites or locations, and transmitting it to collectors at receiving site for monitoring, analyzing, and driving improvement actions. This book provides the necessary knowledge and information to understand the telemetry infrastructure and associated details. It will enable readers to implement a telemetry program to address customer experience pain and improve customer experience. The authors of this book have all served in different roles and capacities in one of Silicon Valleys premier technology companies. These roles include software engineering, customer assurance, quality management, technology development, and implementation. Their paths intersected in the area of quality management, and they have witnessed first-hand how the latest technology/market transitions around Internet of Things (IoT), digitization, and telemetry are impacting the company they work, as well as the high-tech industry and global economy as a whole. The real-time nature of data and the advent of machine-learning algorithms have set the stage for a new era that the authors call adaptive customer experience. The premise of this concept is that real-time availability of customer experience data opens the door for real-time responses based on machine-learning algorithms. This creates an unprecedented opportunity to change the relationship between customers and the systems they depend on in their digital world. The proliferation of sensors and improvements in data science capabilities are creating an environment where the possibilities for telemetry are limitless. The book provides several examples of use cases and applications that help bring telemetry to life. |
| data scientist mckinsey salary: Concise Guide to Databases Peter Lake, Paul Crowther, 2013-11-22 This easy-to-read textbook/reference presents a comprehensive introduction to databases, opening with a concise history of databases and of data as an organisational asset. As relational database management systems are no longer the only database solution, the book takes a wider view of database technology, encompassing big data, NoSQL, object and object-relational and in-memory databases. The text also examines the issues of scalability, availability, performance and security encountered when building and running a database in the real world. Topics and features: presents review and discussion questions at the end of each chapter, in addition to skill-building, hands-on exercises; introduces the fundamental concepts and technologies in database systems, placing these in an historic context; describes the challenges faced by database professionals; reviews the use of a variety of database types in business environments; discusses areas for further research within this fast-moving domain. |
| data scientist mckinsey salary: Closing the Analytics Talent Gap Jennifer Priestley, Robert McGrath, 2021-05-03 How can we recruit out of your program? We have a project – how do we reach out to your students? If we do research together who owns it? We have employees who need to upskill in analytics – can you help me with that? How much does all of this cost? Managers and executives are increasingly asking university professors such questions as they deal with a critical shortage of skilled data analysts. At the same time, academics are asking such questions as: How can I bring a real analytical project in the classroom? How can I get real data to help my students develop the skills necessary to be a data scientist? Is what I am teaching in the classroom aligned with the demands of the market for analytical talent? After spending several years answering almost daily e-mails and telephone calls from business managers asking for staffing help and aiding fellow academics with their analytics teaching needs, Dr. Jennifer Priestley of Kennesaw State University and Dr. Robert McGrath of the University of New Hampshire wrote Closing the Analytics Talent Gap: An Executive’s Guide to Working with Universities. The book builds a bridge between university analytics programs and business organizations. It promotes a dialog that enables executives to learn how universities can help them find strategically important personnel and universities to learn how they can develop and educate this personnel. Organizations are facing previously unforeseen challenges related to the translation of massive amounts of data – structured and unstructured, static and in-motion, voice, text, and image – into information to solve current challenges and anticipate new ones. The advent of analytics and data science also presents universities with unforeseen challenges of providing learning through application. This book helps both organizations with finding data natives and universities with educating students to develop the facility to work in a multi-faceted and complex data environment. . |
| data scientist mckinsey salary: The Visual Imperative Lindy Ryan, 2016-03-14 Data is powerful. It separates leaders from laggards and it drives business disruption, transformation, and reinvention. Today's most progressive companies are using the power of data to propel their industries into new areas of innovation, specialization, and optimization. The horsepower of new tools and technologies have provided more opportunities than ever to harness, integrate, and interact with massive amounts of disparate data for business insights and value – something that will only continue in the era of the Internet of Things. And, as a new breed of tech-savvy and digitally native knowledge workers rise to the ranks of data scientist and visual analyst, the needs and demands of the people working with data are changing, too. The world of data is changing fast. And, it's becoming more visual. Visual insights are becoming increasingly dominant in information management, and with the reinvigorated role of data visualization, this imperative is a driving force to creating a visual culture of data discovery. The traditional standards of data visualizations are making way for richer, more robust and more advanced visualizations and new ways of seeing and interacting with data. However, while data visualization is a critical tool to exploring and understanding bigger and more diverse and dynamic data, by understanding and embracing our human hardwiring for visual communication and storytelling and properly incorporating key design principles and evolving best practices, we take the next step forward to transform data visualizations from tools into unique visual information assets. - Discusses several years of in-depth industry research and presents vendor tools, approaches, and methodologies in discovery, visualization, and visual analytics - Provides practicable and use case-based experience from advisory work with Fortune 100 and 500 companies across multiple verticals - Presents the next-generation of visual discovery, data storytelling, and the Five Steps to Data Storytelling with Visualization - Explains the Convergence of Visual Analytics and Visual discovery, including how to use tools such as R in statistical and analytic modeling - Covers emerging technologies such as streaming visualization in the IOT (Internet of Things) and streaming animation |
| data scientist mckinsey salary: Open Data for Education Dmitry Mouromtsev, Mathieu d’Aquin, 2016-03-18 This volume comprises a collection of papers presented at an Open Data in Education Seminar and the LILE workshops during 2014-2015. In the first part of the book, two chapters give different perspectives on the current use of linked and open data in education, including the use of technology and the topics that are being covered. The second part of the book focuses on the specific, practical applications that are being put in place to exploit open and linked data in education today. The goal of this book is to provide a snapshot of current activities, and to share and disseminate the growing collective experience on open and linked data in education. This volume brings together research results, studies, and practical endeavors from initiatives spread across several countries around the world. These initiatives are laying the foundations of open and linked data in the education movement and leading the way through innovative applications. |
| data scientist mckinsey salary: Transforming the Healthcare Revenue Cycle with Artificial Intelligence Korin Reid, 2025-08-08 Revenue cycle management (RCM) refers to an institution’s financial management process that helps track, identify, collect, and manage incoming payments. This process helps businesses foster financial transparency within the company and charge patients the correct amount for the services they receive. But because of the unique healthcare payment system in the United States, relatively few of these dollars change hands directly between providers and their patients. Instead, there is a complex reimbursement system, mostly driven by third-party payment transactions between government programs and insurance companies, on the one hand, and healthcare providers, on the other. Artificial intelligence (AI) can help predict claim denials by analyzing past denial trends and alerting health information management (HIM) professionals of potential denials in advance of billing. This affords an opportunity to review and correct claims pre-bill. One major benefit of AI in RCM is increased efficiency. By automating routine tasks, healthcare organizations can free up staff to focus on more important and value-added work. This can lead to improved productivity and faster turnaround times, ultimately resulting in improved patient care. This book provides an informative blueprint to help hospital and healthcare revenue cycle administration personnel along their AI journey by using the most commonly available administrative datasets, electronic claims, and electronic health records. Peppered throughout the book are hilarious anecdotes and cautionary tales from the author’s experience in building AI solutions in the healthcare space. The book begins with an overview of key concepts such as data science, machine learning, AI, language models (e.g., ChatGPT), and more. The author expands on the defined process in the context of common revenue cycle use cases that leverage electronic claims and electronic health records. Finally, the book provides guidance on how to evaluate AI solutions at each point of the development process, including third-party vendor AI solutions. |
| data scientist mckinsey salary: Accelerate Nicole Forsgren, PhD, Jez Humble, Gene Kim, 2018-03-27 Winner of the Shingo Publication Award Accelerate your organization to win in the marketplace. How can we apply technology to drive business value? For years, we've been told that the performance of software delivery teams doesn't matter―that it can't provide a competitive advantage to our companies. Through four years of groundbreaking research to include data collected from the State of DevOps reports conducted with Puppet, Dr. Nicole Forsgren, Jez Humble, and Gene Kim set out to find a way to measure software delivery performance―and what drives it―using rigorous statistical methods. This book presents both the findings and the science behind that research, making the information accessible for readers to apply in their own organizations. Readers will discover how to measure the performance of their teams, and what capabilities they should invest in to drive higher performance. This book is ideal for management at every level. |
| data scientist mckinsey salary: Analytics of Life Mert Damlapinar, 2019-11-11 Analytics of Life provides the reader with a broad overview of the field of data analytics and artificial intelligence. It provides the layperson an understanding of the various stages of artificial intelligence, the risks and powerful benefits. And it provides a way to look at big data and machine learning that enables us to make the most of this exciting new realm of technology in our day-to-day jobs and our small businesses. Questions you can find answers* * What is artificial intelligence (AI)? * What is the difference between AI, machine learning and data analytics? * Which jobs AI will replace, which jobs are safe from data analytics revolution? * Why data analytics is the best career move? * How can I apply data analytics in my job or small business? Who is this book for? * Managers and business professionals * Marketers, product managers, and business strategists * Entrepreneurs, founders and startups team members * Consultants, advisors and educators * Almost anybody who has an interest in the future According to an article by Cade Metz in The New York Times, Researchers say computer systems are learning from lots and lots of digitized books and news articles that could bake old attitudes into new technology. Oxford University professor Nick Bostrom argues that if machine brains surpassed human brains in general intelligence, then this new superintelligence could become extremely powerful - possibly beyond our control. MIT professor Max Tegmark describes and illuminates the recent, ground-breaking advances in Artificial Intelligence and how it might overtake human intelligence. As Oxford University economist Daniel Susskind points out, technological progress could bring about unprecedented prosperity, solving one of humanity's oldest problems: how to make sure that everyone has enough to live on. Distinguished AI researcher and professor of computer science at UC Berkeley, Russell Stuart suggests that we can rebuild AI on a new foundation, according to which machines are designed to be inherently uncertain about the human preferences they are required to satisfy. Industry experts claim that AI will have a negative impact on blue-collar jobs, but Mert predicts that Americans and Europeans will experience a strong impact on white-collar jobs as well. And Mert also provides research results and a clear description of which jobs will be affected and how soon, which jobs could be enhanced with AI. Analytics of Life also provides solutions and insight into some of the most profound changes to come in human history. |
| data scientist mckinsey salary: News for the Rich, White, and Blue Nikki Usher, 2021-07-06 As cash-strapped metropolitan newspapers struggle to maintain their traditional influence and quality reporting, large national and international outlets have pivoted to serving readers who can and will choose to pay for news, skewing coverage toward a wealthy, white, and liberal audience. Amid rampant inequality and distrust, media outlets have become more out of touch with the democracy they purport to serve. How did journalism end up in such a predicament, and what are the prospects for achieving a more equitable future? In News for the Rich, White, and Blue, Nikki Usher recasts the challenges facing journalism in terms of place, power, and inequality. Drawing on more than a decade of field research, she illuminates how journalists decide what becomes news and how news organizations strategize about the future. Usher shows how newsrooms remain places of power, largely white institutions growing more elite as journalists confront a shrinking job market. She details how Google, Facebook, and the digital-advertising ecosystem have wreaked havoc on the economic model for quality journalism, leaving local news to suffer. Usher also highlights how the handful of likely survivors—well-funded media outlets such as the New York Times—increasingly appeal to a global, “placeless” reader. News for the Rich, White, and Blue concludes with a series of provocative recommendations to reimagine journalism to ensure its resiliency and its ability to speak to a diverse set of issues and readers. |
| data scientist mckinsey salary: Minding the Machines Jeremy Adamson, 2021-06-25 Organize, plan, and build an exceptional data analytics team within your organization In Minding the Machines: Building and Leading Data Science and Analytics Teams, AI and analytics strategy expert Jeremy Adamson delivers an accessible and insightful roadmap to structuring and leading a successful analytics team. The book explores the tasks, strategies, methods, and frameworks necessary for an organization beginning their first foray into the analytics space or one that is rebooting its team for the umpteenth time in search of success. In this book, you’ll discover: A focus on the three pillars of strategy, process, and people and their role in the iterative and ongoing effort of building an analytics team Repeated emphasis on three guiding principles followed by successful analytics teams: start early, go slow, and fully commit The importance of creating clear goals and objectives when creating a new analytics unit in an organization Perfect for executives, managers, team leads, and other business leaders tasked with structuring and leading a successful analytics team, Minding the Machines is also an indispensable resource for data scientists and analysts who seek to better understand how their individual efforts fit into their team’s overall results. |
| data scientist mckinsey salary: Negotiating Your Salary Jack Chapman, 2000 Proving your worth to a potential employer can begin well before the negotiating interview - that's why you need to be prepared. For 15 years, Negotiating Your Salary has been the bible for salary negotiations and, updated for the new millennium, this classic is back to coach a new generation of job hunters. Renowned career advisor Jack Chapman teaches you when to bring up the salary issue, how to respond to interviewers' offers, and simple strategies to help double your salary. For the already employed, he also covers how to make the most of raises and salary reviews, and much more. |
| data scientist mckinsey salary: DATAMATION DP SALARY SURVEY JANUARY 1975 , 1975 |
| data scientist mckinsey salary: Artificial Intelligence for Marketing Jim Sterne, 2017-08-02 A straightforward, non-technical guide to the next major marketing tool Artificial Intelligence for Marketing presents a tightly-focused introduction to machine learning, written specifically for marketing professionals. This book will not teach you to be a data scientist—but it does explain how Artificial Intelligence and Machine Learning will revolutionize your company's marketing strategy, and teach you how to use it most effectively. Data and analytics have become table stakes in modern marketing, but the field is ever-evolving with data scientists continually developing new algorithms—where does that leave you? How can marketers use the latest data science developments to their advantage? This book walks you through the need-to-know aspects of Artificial Intelligence, including natural language processing, speech recognition, and the power of Machine Learning to show you how to make the most of this technology in a practical, tactical way. Simple illustrations clarify complex concepts, and case studies show how real-world companies are taking the next leap forward. Straightforward, pragmatic, and with no math required, this book will help you: Speak intelligently about Artificial Intelligence and its advantages in marketing Understand how marketers without a Data Science degree can make use of machine learning technology Collaborate with data scientists as a subject matter expert to help develop focused-use applications Help your company gain a competitive advantage by leveraging leading-edge technology in marketing Marketing and data science are two fast-moving, turbulent spheres that often intersect; that intersection is where marketing professionals pick up the tools and methods to move their company forward. Artificial Intelligence and Machine Learning provide a data-driven basis for more robust and intensely-targeted marketing strategies—and companies that effectively utilize these latest tools will reap the benefit in the marketplace. Artificial Intelligence for Marketing provides a nontechnical crash course to help you stay ahead of the curve. |
| data scientist mckinsey salary: Case Interview Secrets Victor Cheng, 2012 Cheng, a former McKinsey management consultant, reveals his proven, insider'smethod for acing the case interview. |
| data scientist mckinsey salary: Bain and Company WetFeet, 2009 |
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| data scientist mckinsey salary: Useful Delusions: The Power and Paradox of the Self-Deceiving Brain Shankar Vedantam, Bill Mesler, 2021-03-02 A Behavioral Scientist Notable Book of 2021 A Next Big Idea Club Best Nonfiction of 2021 From the New York Times best-selling author and host of Hidden Brain comes a thought-provoking look at the role of self-deception in human flourishing. Self-deception does terrible harm to us, to our communities, and to the planet. But if it is so bad for us, why is it ubiquitous? In Useful Delusions, Shankar Vedantam and Bill Mesler argue that, paradoxically, self-deception can also play a vital role in our success and well-being. The lies we tell ourselves sustain our daily interactions with friends, lovers, and coworkers. They can explain why some people live longer than others, why some couples remain in love and others don’t, why some nations hold together while others splinter. Filled with powerful personal stories and drawing on new insights in psychology, neuroscience, and philosophy, Useful Delusions offers a fascinating tour of what it really means to be human. |
| data scientist mckinsey salary: Bullshit Jobs David Graeber, 2019-05-07 From David Graeber, the bestselling author of The Dawn of Everything and Debt—“a master of opening up thought and stimulating debate” (Slate)—a powerful argument against the rise of meaningless, unfulfilling jobs…and their consequences. Does your job make a meaningful contribution to the world? In the spring of 2013, David Graeber asked this question in a playful, provocative essay titled “On the Phenomenon of Bullshit Jobs.” It went viral. After one million online views in seventeen different languages, people all over the world are still debating the answer. There are hordes of people—HR consultants, communication coordinators, telemarketing researchers, corporate lawyers—whose jobs are useless, and, tragically, they know it. These people are caught in bullshit jobs. Graeber explores one of society’s most vexing and deeply felt concerns, indicting among other villains a particular strain of finance capitalism that betrays ideals shared by thinkers ranging from Keynes to Lincoln. “Clever and charismatic” (The New Yorker), Bullshit Jobs gives individuals, corporations, and societies permission to undergo a shift in values, placing creative and caring work at the center of our culture. This book is for everyone who wants to turn their vocation back into an avocation and “a thought-provoking examination of our working lives” (Financial Times). |
| data scientist mckinsey salary: The Internet Encyclopedia Hossein Bidgoli, 2004 The Internet Encyclopedia in a 3-volume reference work on the internet as a business tool, IT platform, and communications and commerce medium. |
| data scientist mckinsey salary: The Consulting Apprenticeship Steve Shu, 2015-07-16 The Consulting Apprenticeship is written for business professionals and consultants with a focus on nuances passed on during apprenticeship regarding consulting delivery. Business professionals can benefit with a jump-start approach to applying consulting principles to their business. Designed for the busy professional, The Consulting Apprenticeship is a book of forty, quick-read ideas. These forty, short chapters are divided into four sections: Consulting Mindset - This section covers consulting ways of thinking and can be adopted by both company personnel and consultants. Consulting Techniques - This section covers specific tactics and toolkit methods when using consultative approaches in the trenches as either a company- or consulting firm-practitioner. Consulting Mastery - This section covers advanced perspectives on consulting and may be more useful to either company personnel evaluating consultants or mid- to senior-level consultants. Consulting Special Situations - Whereas the prior sections are applicable to a wide variety of situations, this section covers more infrequent, specific business situations involving consultative approaches in the trenches as either a company- or consulting firm-practitioner. Each chapter of the book concludes with an optional, takeaway exercise. The exercises vary widely in terms of level of involvement. For example, in some cases you can refer to online material. In other cases, you can engage in deeper thinking or apply the concepts over an extended period of time. However you choose to use this book, consulting mastery is a lifelong pursuit. I hope this book helps you with your journey. Stephen Shu Praise for The Consulting Apprenticeship When one of the companies I worked for needed help taking its consulting organization to the next level, I hired Steve Shu. His ability to drive our management team - all with different opinions on what we should or should not do - to a 'so-what' conclusion and pragmatic next steps gave us the jump start we needed. He is one of the best and deeply understands how consulting organizations should work. His book provides great techniques as well as tools you can use immediately. - Prakash Panjwani, CEO at WatchGuard Technologies, former President and CEO of SafeNet Steve Shu has put together a comprehensive guide to the all-important nuts and bolts of being a great consultant. The information in Chapter 21, 'Eight Secret Weapons of the Modern Consultant, ' is worth the price of the book. If you're serious about being a more effective consultant, read this book. - Michael McLaughlin, Author of Winning the Professional Services Sale and Principal Consultant at MindShare Consulting LLC; former Partner at Deloitte Steve Shu has written a hands-on, highly practical guide for new management consultants and internal corporate business strategists alike. So many projects fail because they do not practice the basic consulting project management hygiene Steve describes in chapter 11. If you are new to the trade and want to greatly increase your chance of delivering successful consulting projects, read this book. - Robert Reppa, Vice President Strategy at Johnson Controls and former Partner at Booz & Company Steve Shu has written a Rosetta Stone for both new and experienced consultants. Filled with forty power-packed ideas and practical chapter takeaways, Consulting Apprenticeship is structured for busy executives to easily digest each concept. A must read for those who seek to go beyond the shallow bromides of the consulting profession, and hone their skills with deeper, more meaningful approaches. - Adrian C. Ott, Award-winning author of The 24-Hour Customer, and CEO, Exponential Edge Inc, called One of Silicon Valley's most respected strategists by Consulting Magazine |
| data scientist mckinsey salary: SpeciaList , 1990 |
| data scientist mckinsey salary: The Medical Science Liaison Career Guide: How to Break Into Your First Role Dr. Samuel Jacob Dyer, 2023-08-21 Even for highly qualified candidates, breaking into the Medical Science Liaison profession is a challenging endeavor. It's nearly impossible to achieve on your own without the proper preparation and guidance. The Medical Science Liaison Career Guide: How to Break Into Your First Role is a step-by-step guide on how to break into the competitive MSL profession. The book provides numerous techniques and effective strategies for distinguishing yourself from other applicants and reveals the secrets of how to successfully search, apply, interview, and ultimately break into your first MSL role. The book also reveals the techniques utilized by 545 MSLs who successfully broke into the profession, as well as the preferences of 185 MSL hiring managers when evaluating applicants. DR. SAMUEL JACOB DYER shares his years of experience as a hiring manager at some of the world's top pharmaceutical companies and as the CEO of the MSL Society. In three sections, he thoroughly explains the MSL role, provides the elements of a successful MSL job search strategy, and demystifies the entire MSL hiring process. Dr. Dyer has coached, interviewed, and reviewed the CVs of countless aspiring MSLs. His insights and guidance have resulted in hundreds of aspiring MSLs successfully breaking into their first roles. |
| data scientist mckinsey salary: Complexity M. Mitchell Waldrop, 2019-10-01 “If you liked Chaos, you’ll love Complexity. Waldrop creates the most exciting intellectual adventure story of the year” (The Washington Post). In a rarified world of scientific research, a revolution has been brewing. Its activists are not anarchists, but rather Nobel Laureates in physics and economics and pony-tailed graduates, mathematicians, and computer scientists from all over the world. They have formed an iconoclastic think-tank and their radical idea is to create a new science: complexity. They want to know how a primordial soup of simple molecules managed to turn itself into the first living cell—and what the origin of life some four billion years ago can tell us about the process of technological innovation today. This book is their story—the story of how they have tried to forge what they like to call the science of the twenty-first century. “Lucidly shows physicists, biologists, computer scientists and economists swapping metaphors and reveling in the sense that epochal discoveries are just around the corner . . . [Waldrop] has a special talent for relaying the exhilaration of moments of intellectual insight.” —The New York Times Book Review “Where I enjoyed the book was when it dove into the actual question of complexity, talking about complex systems in economics, biology, genetics, computer modeling, and so on. Snippets of rare beauty here and there almost took your breath away.” —Medium “[Waldrop] provides a good grounding of what may indeed be the first flowering of a new science.” —Publishers Weekly |
| data scientist mckinsey salary: New Scientist , 1999 |
| data scientist mckinsey salary: How I Became a Quant Richard R. Lindsey, Barry Schachter, 2011-01-11 Praise for How I Became a Quant Led by two top-notch quants, Richard R. Lindsey and Barry Schachter, How I Became a Quant details the quirky world of quantitative analysis through stories told by some of today's most successful quants. For anyone who might have thought otherwise, there are engaging personalities behind all that number crunching! --Ira Kawaller, Kawaller & Co. and the Kawaller Fund A fun and fascinating read. This book tells the story of how academics, physicists, mathematicians, and other scientists became professional investors managing billions. --David A. Krell, President and CEO, International Securities Exchange How I Became a Quant should be must reading for all students with a quantitative aptitude. It provides fascinating examples of the dynamic career opportunities potentially open to anyone with the skills and passion for quantitative analysis. --Roy D. Henriksson, Chief Investment Officer, Advanced Portfolio Management Quants--those who design and implement mathematical models for the pricing of derivatives, assessment of risk, or prediction of market movements--are the backbone of today's investment industry. As the greater volatility of current financial markets has driven investors to seek shelter from increasing uncertainty, the quant revolution has given people the opportunity to avoid unwanted financial risk by literally trading it away, or more specifically, paying someone else to take on the unwanted risk. How I Became a Quant reveals the faces behind the quant revolution, offering you?the?chance to learn firsthand what it's like to be a?quant today. In this fascinating collection of Wall Street war stories, more than two dozen quants detail their roots, roles, and contributions, explaining what they do and how they do it, as well as outlining the sometimes unexpected paths they have followed from the halls of academia to the front lines of an investment revolution. |
| data scientist mckinsey salary: How Learning Works Susan A. Ambrose, Michael W. Bridges, Michele DiPietro, Marsha C. Lovett, Marie K. Norman, 2010-04-16 Praise for How Learning Works How Learning Works is the perfect title for this excellent book. Drawing upon new research in psychology, education, and cognitive science, the authors have demystified a complex topic into clear explanations of seven powerful learning principles. Full of great ideas and practical suggestions, all based on solid research evidence, this book is essential reading for instructors at all levels who wish to improve their students' learning. —Barbara Gross Davis, assistant vice chancellor for educational development, University of California, Berkeley, and author, Tools for Teaching This book is a must-read for every instructor, new or experienced. Although I have been teaching for almost thirty years, as I read this book I found myself resonating with many of its ideas, and I discovered new ways of thinking about teaching. —Eugenia T. Paulus, professor of chemistry, North Hennepin Community College, and 2008 U.S. Community Colleges Professor of the Year from The Carnegie Foundation for the Advancement of Teaching and the Council for Advancement and Support of Education Thank you Carnegie Mellon for making accessible what has previously been inaccessible to those of us who are not learning scientists. Your focus on the essence of learning combined with concrete examples of the daily challenges of teaching and clear tactical strategies for faculty to consider is a welcome work. I will recommend this book to all my colleagues. —Catherine M. Casserly, senior partner, The Carnegie Foundation for the Advancement of Teaching As you read about each of the seven basic learning principles in this book, you will find advice that is grounded in learning theory, based on research evidence, relevant to college teaching, and easy to understand. The authors have extensive knowledge and experience in applying the science of learning to college teaching, and they graciously share it with you in this organized and readable book. —From the Foreword by Richard E. Mayer, professor of psychology, University of California, Santa Barbara; coauthor, e-Learning and the Science of Instruction; and author, Multimedia Learning |
| data scientist mckinsey salary: Beyond The Mba Hype Sameer Kamat, 2011-09-08 An updated and revised edition of the bestselling book This is a revised and updated edition of this bestselling book with useful new material to guide the MBA aspirant - the working executive as well as the fresh college graduate - on doing MBA from abroad. Most Indian MBA applicants are completely at sea when it comes to approaching international education opportunities. This is primarily because the MBA selection process and the parameters considered by the top business schools abroad for admitting candidates into their fold are very different from what we are used to. Beyond the MBA Hype talks about the typical issues, challenges and dilemmas that Indian applicants grapple with when it comes to international MBA programmes. |
| data scientist mckinsey salary: Grit Angela Duckworth, 2016-05-03 In this instant New York Times bestseller, Angela Duckworth shows anyone striving to succeed that the secret to outstanding achievement is not talent, but a special blend of passion and persistence she calls “grit.” “Inspiration for non-geniuses everywhere” (People). The daughter of a scientist who frequently noted her lack of “genius,” Angela Duckworth is now a celebrated researcher and professor. It was her early eye-opening stints in teaching, business consulting, and neuroscience that led to her hypothesis about what really drives success: not genius, but a unique combination of passion and long-term perseverance. In Grit, she takes us into the field to visit cadets struggling through their first days at West Point, teachers working in some of the toughest schools, and young finalists in the National Spelling Bee. She also mines fascinating insights from history and shows what can be gleaned from modern experiments in peak performance. Finally, she shares what she’s learned from interviewing dozens of high achievers—from JP Morgan CEO Jamie Dimon to New Yorker cartoon editor Bob Mankoff to Seattle Seahawks Coach Pete Carroll. “Duckworth’s ideas about the cultivation of tenacity have clearly changed some lives for the better” (The New York Times Book Review). Among Grit’s most valuable insights: any effort you make ultimately counts twice toward your goal; grit can be learned, regardless of IQ or circumstances; when it comes to child-rearing, neither a warm embrace nor high standards will work by themselves; how to trigger lifelong interest; the magic of the Hard Thing Rule; and so much more. Winningly personal, insightful, and even life-changing, Grit is a book about what goes through your head when you fall down, and how that—not talent or luck—makes all the difference. This is “a fascinating tour of the psychological research on success” (The Wall Street Journal). |
| data scientist mckinsey salary: Invisible Women Caroline Criado Perez, 2019-03-12 #1 International Bestseller “A rallying cry to fight back.” —Sunday Times (London) Winner, 2019 Financial Times and McKinsey Business Book of the Year Award Winner, 2019 Royal Society Science Book Prize Data is fundamental to the modern world. From economic development, to healthcare, to education and public policy, we rely on numbers to allocate resources and make crucial decisions. But because so much data fails to take into account gender, because it treats men as the default and women as atypical, bias and discrimination are baked into our systems. And women pay tremendous costs for this bias in time, money, and sometimes with their lives. Celebrated feminist advocate Caroline Criado Perez investigates the shocking root cause of gender inequality and research in Invisible Women, diving into women’s lives at home, the workplace, the public square, the doctor’s office, and more. Chapters here include: Can Snow-Clearing Be Sexist The Myth of Meritocracy The Henry Higgins Effect One-Size-Fits-Men Yentl Syndrome From Purse to Wallet Women’s Rights Are Human Rights Perez writes in her preface, “It’s when women are able to step out from the shadows with their voices and their bodies that things start to shift. The gaps close. And so, at heart, Invisible Women is also a call for change. For too long we have positioned women as a deviation from standard humanity and this is why they have been allowed to become invisible. It’s time for a change in perspective. It’s time for women to be seen.” Built on hundreds of studies in the US, the UK, and around the world, and written with energy, wit, and sparkling intelligence, this is a groundbreaking, unforgettable exposé that will change the way you look at the world. |
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the …
Belmont Forum Adopts Open Data Principles for Environme…
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues …
Mosquitoes populations modelling for early warning s…
Jun 10, 2020 · This technology will include the use of mobile surveillance apps using gamification and citizen …
Climate-Induced Migration in Africa and Beyond: Big Data a…
CLIMB will also leverage earth observation and social media data, and combine them with survey and …
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will enable a …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Mosquitoes populations modelling for early warning system and …
Jun 10, 2020 · This technology will include the use of mobile surveillance apps using gamification and citizen science technology co-developed with local stakeholders for reporting locations of …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Data and Digital Outputs Management Annex (Full)
Released 5 May, 2017 This is the official Data and Digital Outputs Management Annex used by the Science Driven e-Infrastructures CRA. Includes questions to be answered during pre …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels to …
Data and Digital Outputs Management Plan Template
Data and Digital Outputs Management Plan to ensure ethical approaches and compliance with the Belmont Forum Open Data Policy and Principles , as well as the F AIR Data Principles …
