Learn what it takes to succeed in the the most in-demand tech job
Harvard Business Review calls it the sexiest tech job of the 21st century. Data scientists are in demand, and this unique book shows you exactly what employers want and the skill set that separates the quality data scientist from other talented IT professionals. Data science involves extracting, creating, and processing data to turn it into business value. With over 15 years of big data, predictive modeling, and business analytics experience, author Vincent Granville is no stranger to data science. In this one-of-a-kind guide, he provides insight into the essential data science skills, such as statistics and visualization techniques, and covers everything from analytical recipes and data science tricks to common job interview questions, sample resumes, and source code.
The applications are endless and varied: automatically detecting spam and plagiarism, optimizing bid prices in keyword advertising, identifying new molecules to fight cancer, assessing the risk of meteorite impact. Complete with case studies, this book is a must, whether you're looking to become a data scientist or to hire one.
Developing Analytic Talent: Becoming a Data Scientist is essential reading for those aspiring to this hot career choice and for employers seeking the best candidates.
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Vincent Granville, Ph.D. is a data scientist with 15 years of big data, predictive modeling, and business analytics experience. He is the co-founder of Data Science Central, which includes a robust editorial platform, social interaction, forum-based technical support, the latest in technology tools and trends, and industry job opportunities.
<p>THE DEFINITIVE JOB SEARCH AND PREPARATION <b>GUIDE FOR DATA SCIENTISTS</b> <p>Data science is one of the hottest disciplines in IT, but much of the talk is just hype. The aspiring data scientist requires a resource that covers the important topics comprehensively and avoids the hype and buzzwords surrounding data science and big data. This book will show you exactly what data science is, how it differs from computer science, how to extract value from data and, most importantly, how to develop your data science skills to obtain employment. <ul> <li>Source code, data sets, and a dictionary for review</li> <li>Sample resumes, salary surveys, and sample job ads for data scientists</li> <li>Detail into what companies are looking for in a data scientist</li> <li>Authoritative analysis of the big data and analytics industry</li> <li>Real-world job interview questions for a competitive advantage</li> <li>Cases studies for understanding analytics in practice</li> <li>Data science tricks, recipes, and rules of thumb</li> </ul>
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