Data Scientists At Work

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Build A Career In Data Science

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Author : Emily Robinson
language : en
Publisher: Simon and Schuster
Release Date : 2020-03-06

Build A Career In Data Science written by Emily Robinson and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-06 with Computers categories.

Summary You are going to need more than technical knowledge to succeed as a data scientist. Build a Career in Data Science teaches you what school leaves out, from how to land your first job to the lifecycle of a data science project, and even how to become a manager. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology What are the keys to a data scientist’s long-term success? Blending your technical know-how with the right “soft skills” turns out to be a central ingredient of a rewarding career. About the book Build a Career in Data Science is your guide to landing your first data science job and developing into a valued senior employee. By following clear and simple instructions, you’ll learn to craft an amazing resume and ace your interviews. In this demanding, rapidly changing field, it can be challenging to keep projects on track, adapt to company needs, and manage tricky stakeholders. You’ll love the insights on how to handle expectations, deal with failures, and plan your career path in the stories from seasoned data scientists included in the book. What's inside Creating a portfolio of data science projects Assessing and negotiating an offer Leaving gracefully and moving up the ladder Interviews with professional data scientists About the reader For readers who want to begin or advance a data science career. About the author Emily Robinson is a data scientist at Warby Parker. Jacqueline Nolis is a data science consultant and mentor. Table of Contents: PART 1 - GETTING STARTED WITH DATA SCIENCE 1. What is data science? 2. Data science companies 3. Getting the skills 4. Building a portfolio PART 2 - FINDING YOUR DATA SCIENCE JOB 5. The search: Identifying the right job for you 6. The application: Résumés and cover letters 7. The interview: What to expect and how to handle it 8. The offer: Knowing what to accept PART 3 - SETTLING INTO DATA SCIENCE 9. The first months on the job 10. Making an effective analysis 11. Deploying a model into production 12. Working with stakeholders PART 4 - GROWING IN YOUR DATA SCIENCE ROLE 13. When your data science project fails 14. Joining the data science community 15. Leaving your job gracefully 16. Moving up the ladder

Data Science Jobs

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Author : Ann Rajaram
language : en
Publisher: JourneyofAnalytics
Release Date :

Data Science Jobs written by Ann Rajaram and has been published by JourneyofAnalytics this book supported file pdf, txt, epub, kindle and other format this book has been release on with Business & Economics categories.

Want a high-paying $$$ career in the exciting field of DataScience? This is the ONLY book that will help you land a lucrative Analytics job in 90 days or less! This book is the perfect guide for you, if you fall into any of these categories: * You recently completed a masters degree (or online course or bootcamp) and want to get hired quickly as a Data Scientist, Data Analyst, Data Engineer, Machine learning engineer or BI developer. * Looking to start a career in data science, but unsure where to start. * You are an experienced tech professional, but looking to pivot into analytics to boost your salary potential. * Tired of applying to dozens of jobs without getting a positive response and/or final job offer . * F1 visa, STEM OPT/ CPT students will also find this book helpful to land a job in this lucrative field. The book will teach you proven successful strategies on: * Winning Profiles Turbocharge your resume and LinkedIn profile and start receiving interview calls from hiring managers. Let JOBS CHASE YOU, instead of the other way around! * LinkedIn - A dedicated chapter on LinkedIn that teaches you some creative (and SECRET) ways to leverage the site and identify high-paying jobs with low competition. * Niche sites - A full list of niche job boards that other candidates have overlooked. These sites have high-$ jobs but lesser competition than the popular job search sites. Upwork - Contrary to popular opinion, Upwork can help you make $$$ in data science jobs. Learn proven techniques to help you bag contracts and start earning, as quickly as next week. * 100+ interview questions asked in real-life data scientist interviews. * Other learner resources and much more... Author is a practicing analytics professional who has worked in Fortune500 Firms like NASDAQ , BlackRock, etc. Unlike most job search books that are written by recruiters or professors, this book is written by a senior professional, who rose quickly from analyst to managerial roles. She has attended interviews of her own, and knows clearly the frustrations (and at times, hopelessness) of the job search process. The systems in this book have successfully helped dozens of job seekers and will work effectively for you too! Read on to launch your dream career! Note, this book is deliberately kept short and precise, so you can quickly read through and start applying these principles, instead of sifting through 500 pages of fluff. This book includes: Data Science interview questions and answers; Help preparing for Machine Learning Interviews; Top 25 Interview Questions for Data Analyst/Scientist roles; An in-depth overview of Data Science Interview Process; How to ace your interview even if you are an Entry level Data Analyst / Data Scientist; Data Science Interview questions for freshers; How and Where to look for jobs; and much more!

Data Scientists At Work

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Author : Sebastian Gutierrez
language : en
Publisher: Apress
Release Date : 2014-12-12

Data Scientists At Work written by Sebastian Gutierrez and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-12 with Computers categories.

Data Scientists at Work is a collection of interviews with sixteen of the world's most influential and innovative data scientists from across the spectrum of this hot new profession. "Data scientist is the sexiest job in the 21st century," according to the Harvard Business Review. By 2018, the United States will experience a shortage of 190,000 skilled data scientists, according to a McKinsey report. Through incisive in-depth interviews, this book mines the what, how, and why of the practice of data science from the stories, ideas, shop talk, and forecasts of its preeminent practitioners across diverse industries: social network (Yann LeCun, Facebook); professional network (Daniel Tunkelang, LinkedIn); venture capital (Roger Ehrenberg, IA Ventures); enterprise cloud computing and neuroscience (Eric Jonas, formerly Salesforce.com); newspaper and media (Chris Wiggins, The New York Times); streaming television (Caitlin Smallwood, Netflix); music forecast (Victor Hu, Next Big Sound); strategic intelligence (Amy Heineike, Quid); environmental big data (André Karpištšenko, Planet OS); geospatial marketing intelligence (Jonathan Lenaghan, PlaceIQ); advertising (Claudia Perlich, Dstillery); fashion e-commerce (Anna Smith, Rent the Runway); specialty retail (Erin Shellman, Nordstrom); email marketing (John Foreman, MailChimp); predictive sales intelligence (Kira Radinsky, SalesPredict); and humanitarian nonprofit (Jake Porway, DataKind). The book features a stimulating foreword by Google's Director of Research, Peter Norvig. Each of these data scientists shares how he or she tailors the torrent-taming techniques of big data, data visualization, search, and statistics to specific jobs by dint of ingenuity, imagination, patience, and passion. Data Scientists at Work parts the curtain on the interviewees’ earliest data projects, how they became data scientists, theirdiscoveries and surprises in working with data, their thoughts on the past, present, and future of the profession, their experiences of team collaboration within their organizations, and the insights they have gained as they get their hands dirty refining mountains of raw data into objects of commercial, scientific, and educational value for their organizations and clients.

Analyzing The Analyzers

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Author : Harlan Harris
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2013-06-10

Analyzing The Analyzers written by Harlan Harris and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-10 with Computers categories.

Despite the excitement around "data science," "big data," and "analytics," the ambiguity of these terms has led to poor communication between data scientists and organizations seeking their help. In this report, authors Harlan Harris, Sean Murphy, and Marck Vaisman examine their survey of several hundred data science practitioners in mid-2012, when they asked respondents how they viewed their skills, careers, and experiences with prospective employers. The results are striking. Based on the survey data, the authors found that data scientists today can be clustered into four subgroups, each with a different mix of skillsets. Their purpose is to identify a new, more precise vocabulary for data science roles, teams, and career paths. This report describes: Four data scientist clusters: Data Businesspeople, Data Creatives, Data Developers, and Data Researchers Cases in miscommunication between data scientists and organizations looking to hire Why "T-shaped" data scientists have an advantage in breadth and depth of skills How organizations can apply the survey results to identify, train, integrate, team up, and promote data scientists

Working With Ai

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Author : Thomas H. Davenport
language : en
Publisher: MIT Press
Release Date : 2022-09-27

Working With Ai written by Thomas H. Davenport and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-27 with Business & Economics categories.

Two management and technology experts show that AI is not a job destroyer, exploring worker-AI collaboration in real-world work settings. This book breaks through both the hype and the doom-and-gloom surrounding automation and the deployment of artificial intelligence-enabled—“smart”—systems at work. Management and technology experts Thomas Davenport and Steven Miller show that, contrary to widespread predictions, prescriptions, and denunciations, AI is not primarily a job destroyer. Rather, AI changes the way we work—by taking over some tasks but not entire jobs, freeing people to do other, more important and more challenging work. By offering detailed, real-world case studies of AI-augmented jobs in settings that range from finance to the factory floor, Davenport and Miller also show that AI in the workplace is not the stuff of futuristic speculation. It is happening now to many companies and workers. These cases include a digital system for life insurance underwriting that analyzes applications and third-party data in real time, allowing human underwriters to focus on more complex cases; an intelligent telemedicine platform with a chat-based interface; a machine learning-system that identifies impending train maintenance issues by analyzing diesel fuel samples; and Flippy, a robotic assistant for fast food preparation. For each one, Davenport and Miller describe in detail the work context for the system, interviewing job incumbents, managers, and technology vendors. Short “insight” chapters draw out common themes and consider the implications of human collaboration with smart systems.

Data Science

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Author : Ajit Roy
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2016-03-14

Data Science written by Ajit Roy and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-14 with categories.

Presently, scientists, engineers, educators, citizens and decision-makers have unprecedented amounts and types of data available to them. Data generates from many sources, including scientific instruments, medical devices, telescopes, microscopes, satellites; digitally-authored media, text, images, audio, and emails; streaming data from weblogs, videos, financial & commercial transactions. Now we are facing challenges in the management of data and knowledge; and data-enabled discovery processes. Therefore, attention is given on the computational, mathematical, and statistical methods for data analysis; and visualization techniques for "making sense" of the data. Data Science is an applied activity and data scientists serve the needs and solve the problems of data users. Data Science is a flourishing industry. Countries and companies around the world are continuously experiencing a rush in the amount of data collected. They are determined to hire experts who can work on their data and improve their lives. Such experts are known by many names and most popular is 'Data Scientist'. Thomas Davenport and D.J. Patil brought the data scientist into the national spotlight terming 'Data Scientist: The Sexiest Job of the 21st Century'. Data Scientists are in high demand. There is simply not enough talent to fill the jobs. According to expert opinion to become a data scientist, you need is to have enough baseline knowledge and experience, and the skill to constantly adapt and learn. Boot camps are the perfect medium for making the transition. Data science is big landscape and self-learning is the necessary skill if anyone wants to become a good data scientist. MOOCs had been Major source of treasure for the data scientist. You can search through this exhaustive list of courses duly reviewed by experts and documented in the book entitled. 'Data Science-A Career Option for 21st Century'.The book is broadly compiled with the following seven chapters and within each chapter there are many points to get the answers of the key questions that are likely to come from the aspiring Data Scientists. Chapter 1: Basic Concept about Data and Data Science Chapter 2: Comparison among Data Scientist and Other Analytic Disciplines Chapter 3: Skill Requirement for Data Scientist's Job Chapter 4: Data Science Courses Offered by Educational Institutions Chapter 5: Big Data Trends, Predictions and Growth in the Next 12 Months - 2016 Chapter 6: Modeling Related to Data Science Chapter 7: Career Outlook for Data Science Professionals Besides, the book contains web addresses, links, tutorials, video, blog posts that will guide one to the right direction to learn and equip oneself to become a successful Data Scientist. The book is an ideal read for budding data scientists who are just getting started in the field. This book will give you the knowledge and insights you need to hit the ground running in this fast-growing field. This is an essential & Perfect for the aspiring data scientists. Every data science job seeking candidate should understand the fundamentals presented in this book. The demand for Analytics skill is going up steadily globally but there is a huge deficit on the supply side. In spite of Big Data Analytics being a 'Hot' job, there are still a large number of unfilled jobs across the globe due to shortage of required skill.This reflects the increasing demand for sophisticated data analysis skills, combining computer programming with statistics, and the growth in the popularity of the term "data science." A McKinsey Global Institute study states that the US will face a shortage of about 190,000 data scientists and 1.5 million managers and analysts who can understand and make decisions using Big Data by 2018.India currently has the acute scarcity of data analytics talent and demand for talent is expected to be on the higher side as more global organizations are outsourcing their work.

Becoming A Data Head

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Author : Alex J. Gutman
language : en
Publisher: John Wiley & Sons
Release Date : 2021-04-13

Becoming A Data Head written by Alex J. Gutman and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-13 with Business & Economics categories.

"Turn yourself into a Data Head. You'll become a more valuable employee and make your organization more successful." Thomas H. Davenport, Research Fellow, Author of Competing on Analytics, Big Data @ Work, and The AI Advantage You've heard the hype around data - now get the facts. In Becoming a Data Head: How to Think, Speak, and Understand Data Science, Statistics, and Machine Learning, award-winning data scientists Alex Gutman and Jordan Goldmeier pull back the curtain on data science and give you the language and tools necessary to talk and think critically about it. You'll learn how to: Think statistically and understand the role variation plays in your life and decision making Speak intelligently and ask the right questions about the statistics and results you encounter in the workplace Understand what's really going on with machine learning, text analytics, deep learning, and artificial intelligence Avoid common pitfalls when working with and interpreting data Becoming a Data Head is a complete guide for data science in the workplace: covering everything from the personalities you’ll work with to the math behind the algorithms. The authors have spent years in data trenches and sought to create a fun, approachable, and eminently readable book. Anyone can become a Data Head—an active participant in data science, statistics, and machine learning. Whether you're a business professional, engineer, executive, or aspiring data scientist, this book is for you.

Handbook Of Education Policy Research

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Author : Lora Cohen-Vogel
language : en
Publisher: American Educational Research Association
Release Date : 2025-07-17

Handbook Of Education Policy Research written by Lora Cohen-Vogel and has been published by American Educational Research Association this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-17 with Education categories.

The second edition of the Handbook of Education Policy Research—the largest volume published in AERA’s history—addresses a variety of policy and contextual issues in early childhood, K–12, and postsecondary education that have received extensive empirical attention during the past 15 years. With the pandemic and social turmoil as a backdrop, the editors build on the breadth and depth of the first edition while expanding the scope of the project to include subjects, methods, theories, and analyses that have contributed powerfully to the study of education policy and politics in the 2010s and 2020s. The field has become more comprehensive and inclusive, and the authors represent a diversity of racial/ethnic and gender identities and intellectual and disciplinary orientations. Most chapters come from multiple authors, reflecting the multi-sourced development of research in education policy since the first volume was published. This compilation consists of 70 chapters and nine commentaries that map past, present, and future directions of the field and richly attend to critical issues of interest to students, researchers, policy makers, and practitioners.

Machine Learning For Decision Sciences With Case Studies In Python

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Author : S. Sumathi
language : en
Publisher: CRC Press
Release Date : 2022-07-08

Machine Learning For Decision Sciences With Case Studies In Python written by S. Sumathi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-08 with Computers categories.

This book provides a detailed description of machine learning algorithms in data analytics, data science life cycle, Python for machine learning, linear regression, logistic regression, and so forth. It addresses the concepts of machine learning in a practical sense providing complete code and implementation for real-world examples in electrical, oil and gas, e-commerce, and hi-tech industries. The focus is on Python programming for machine learning and patterns involved in decision science for handling data. Features: Explains the basic concepts of Python and its role in machine learning. Provides comprehensive coverage of feature engineering including real-time case studies. Perceives the structural patterns with reference to data science and statistics and analytics. Includes machine learning-based structured exercises. Appreciates different algorithmic concepts of machine learning including unsupervised, supervised, and reinforcement learning. This book is aimed at researchers, professionals, and graduate students in data science, machine learning, computer science, and electrical and computer engineering.

Data Science Job

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Author : Przemek Chojecki
language : en
Publisher: Independently Published
Release Date : 2020-01-29

Data Science Job written by Przemek Chojecki and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-29 with categories.

We're living in a digital world. Most of our global economy is digital and the sheer volume of data is stupendous. It's 2020 and we're living in the future. Data Scientist is one of the hottest job on the market right now. Demand for data science is huge and will only grow, and it seems like it will grow much faster than the actual number of data scientists.So if you want to make a career change and become a data scientist, now is the time.This book will guide you through the process. From my experience of working with multiple companies as a project manager, a data science consultant or a CTO, I was able to see the process of hiring data scientists and building data science teams. I know what's important to land your first job as a data scientist, what skills you should acquire, what you should show during a job interview.