Sebastian Gutierrez Data Scientists at Work

ISBN 13: 9781430265986

Data Scientists at Work

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9781430265986: Data Scientists at Work

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); oceanographic 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). 
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, 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.

Readers will learn:

  • How the data scientists arrived at their positions and what advice they have for others
  • What projects the data scientists work on and the techniques and tools they apply
  • How to frame problems that data science can solve
  • Where data scientists think the most exciting opportunities lie in the future of data science
  • How data scientists add value to their organizations and help people around the world

Who this book is for
The 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.

Table of ContentsChapter 1. Chris Wiggins (The New York Times)
Chapter 2. Caitlin Smallwood (Netflix)
Chapter 3. Yann LeCun (Facebook)
Chapter 4. Erin Shellman (Nordstrom)
Chapter 5. Daniel Tunkelang (LinkedIn)
Chapter 6. John Foreman (MailChimp)
Chapter 7. Roger Ehrenberg (IA Ventures)
Chapter 8. Claudia Perlich (Dstillery)
Chapter 9. Jonathan Lenaghan (PlaceIQ)
Chapter 10. Anna Smith (Rent The Runway)
Chapter 11. Andre Karpistsenko (Planet OS)
Chapter 12. Amy Heineike (Quid)
Chapter 13. Victor Hu (Next Big Sound)
Chapter 14. Kira Radinsky (SalesPredict)
Chapter 15. Eric Jonas (Independent Scientist)
Chapter 16. Jake Porway (DataKind)

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About the Author:

Sebastian Gutierrez is a data entrepreneur who has founded three data-related companies: DataYou (data science and data visualization consulting and education), LetsWombat (data-driven product sampling), and Acheevmo (athletic performance statistics). He was formerly an emerging markets risk manager at Scotia Capital and an FX options trader at JP Morgan and Standard Chartered Bank.Gutierrez provides training in data visualization and D3.js to a diverse client base, including corporations such as the New York Stock Exchange, the American Express Company, and General Dynamics, universities, media agencies, and startups. He leads the 1,600-member New York City D3.js Meetup Group and is co-editor of Data Science Weekly, a weekly newsletter providing curated articles and videos on the latest developments in data science. He is a frequent speaker at meetups and conferences, such as Strata and Hadoop World in New York and Barcelona. He is a cross-disciplinary instructor at General Assembly. Gutierrez holds a BS in Mathematics from MIT and an MA in Economics from the University of San Francisco.

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