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Interviews with Data Scientists is a collection of interviews with twenty-four 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:

* online dating (Thomas Levi, Plenty of Fish)

* Web data extraction (Ignacio Elola, Import.io)

* E-commerce(Dr Andrew Clegg, Etsy)

* Intellectual Property and the Blockchain (Trent McConaghy, Ascribe)

*Geoscience big data (Matt Hall, Agile Geoscience)

* Data tool development (Hadley Wickham, RStudio)

* E-commerce and consultancy (Jeroen Latour, Booking.com and formerly IBM)

* Insurance and FinTech (Jon Sedar, Applied.AI)

* Data Science Consultancy (Ian Huston, Pivotal Labs)

* E-Commerce and Product Analytics (Cameron Davidson-Pilon, Shopify)

* TelCo and Consumer Tech (Shane Lynn, KillBiller)

* E-commerce and Marketing Analytics (Vanessa Sabino, Shopify)

* Supply Chain Management (Peadar Coyle, Formerly of Amazon.com)

* Academic Research and Hedge Funds (Professor David Hand, Imperial College London and Winton Capital)

* Insurance and Re-Insurance (J.D. Long, Renaissance Re); Music Streaming (Erik Bernhardsson, Formerly Spotify);

* Natural Language Processing (Ian Ozsvald, ModelInsight)

* Crowd-sourced Hedge Fund and Trading algortihms (Thomas Wiecki, Quantopian Inc)

* FinTech (Natalie Hockham, GoCardless)

* FoodTech and Sports (Trey Causey, Sports Analytics Consultant and ChefSteps)

* Data Mining Consultancy (Rosaria Silipo, DMR)

* Fashion E-commerce (Brad Klingerberg, Stitch Fix)

* Scalable Machine Learning (Alice Zheng, Dato)

* Publishing (Maria Mestre, Skimlinks)

* Marketing Analytics (Kevin Hillstrom, MineTheData formerly Nordstrom)

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. Interview with Data Scientists 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

The ideal audience is specialists in big data, but we expect interest from HR, Recruiters and Managers. ‘Big Data’ and ‘Data Science’ are too important to only be left to the experts.

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