{"product_id":"9781430265993","title":"Data Scientists at Work","description":"\u003cp\u003e    \u003c\/p\u003e\u003cp\u003e\u003ci\u003e\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003eData Scientists at Work\u003c\/i\u003e 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 \u003ci\u003eHarvard Business Review\u003c\/i\u003e. By 2018, the United States will experience a shortage of 190,000 skilled data scientists, according to a McKinsey report.\u003c\/p\u003e\u003cp\u003eThrough 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\u003cstrong\u003e, \u003c\/strong\u003ePlanet 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.\u003c\/p\u003eEach 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. \u003ci\u003eData Scientists at Work\u003c\/i\u003e parts the curtain on the interviewees’ earliest data projects, how they became data scientists, their discoveries 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. \u003cp\u003e\u003c\/p\u003e         What you’ll learn\u003cp\u003eReaders will learn:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eHow the data scientists arrived at their positions and what advice they have for others\u003c\/li\u003e\n\u003cli\u003eWhat projects the data scientists work on and the techniques and tools they apply\u003c\/li\u003e\n\u003cli\u003eHow to frame problems that data science can solve\u003c\/li\u003e\n\u003cli\u003eWhere data scientists think the most exciting opportunities lie in the future of data science\u003c\/li\u003e\n\u003cli\u003eHow data scientists add value to their organizations and help people around the world\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003eWho this book is for      \u003cp\u003e     \u003c\/p\u003e\u003cp\u003eThe primary readership for this book is general-interest readers interested in this hot new profession and in the nature of the people who work up the readers’ own data trails. The secondary readerships are (a) scientists, mathematicians, and students in feeder disciplines who are interested in scouting the vocational prospects and daily working conditions of data scientists with a view to becoming data scientists themselves, and (b) of business colleagues and managers seeking to understand and collaborate with data scientists to integrate their data management and interpretation capabilities into the competitive intelligence capabilities of the enterprise.\u003c\/p\u003e           Table of Contents\u003cp\u003eChapter 1. Chris Wiggins (The New York Times)\u003c\/p\u003e\u003cp\u003eChapter 2. Caitlin Smallwood (Netflix)\u003c\/p\u003e\u003cp\u003eChapter 3. Yann LeCun (Facebook)\u003c\/p\u003e\u003cp\u003eChapter 4. Erin Shellman (Nordstrom)\u003c\/p\u003e\u003cp\u003eChapter 5. Daniel Tunkelang (LinkedIn)\u003c\/p\u003e\u003cp\u003eChapter 6. John Foreman (MailChimp)\u003c\/p\u003e\u003cp\u003eChapter 7. Roger Ehrenberg (IA Ventures)\u003c\/p\u003e\u003cp\u003eChapter 8. Claudia Perlich (Dstillery)\u003c\/p\u003e\u003cp\u003eChapter 9. Jonathan Lenaghan (PlaceIQ)\u003c\/p\u003e\u003cp\u003eChapter 10. Anna Smith (Rent The Runway)\u003c\/p\u003e\u003cp\u003eChapter 11. Andre Karpistsenko (Planet OS)\u003c\/p\u003e\u003cp\u003eChapter 12. Amy Heineike (Quid)\u003c\/p\u003e\u003cp\u003eChapter 13. Victor Hu (Next Big Sound)\u003c\/p\u003e\u003cp\u003eChapter 14. Kira Radinsky (SalesPredict)\u003c\/p\u003e\u003cp\u003eChapter 15. Eric Jonas (Independent Scientist)\u003c\/p\u003e\u003cp\u003eChapter 16. Jake Porway (DataKind)\u003c\/p\u003e","brand":"Apress","offers":[{"title":"Default Title","offer_id":47174122078448,"sku":"9781430265993","price":23.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0737\/7593\/9824\/files\/9781430265993_p0.jpg?v=1763749440","url":"https:\/\/shop-qa.barnesandnoble.com\/products\/9781430265993","provider":"Barnes \u0026 Noble (DEV)","version":"1.0","type":"link"}