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 (Andre Karpis ts enko 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.
