Data Scientists at Work 1st ed. Edition

This book is awful. I'm not sure whether blame lies with the author, for making the prose so dry, clunky, and literal (as in, the author left in every single instance of the word "like" and "so" and "literally," all of which were liberally used by the yuppies he interviewed) , or with the subjects, for being so vapid and cliche. Every subject in the book feels saturated with marketing-speak and sales-talk, and many of the scientists interviewed are focused on making the rich and affluent even more rich and even more affluent. A few of the subjects give lip service to doing something meaningful, but as each reveals their perspective, you realize that none has ever given a single thought to issues of social justice, the ethical dubiousness of abandoning a scientific or research job to chase after dollars in advertising and getting those who have plenty to buy more, or the moral responsibility that intelligent individuals have to society to do something productive, not just be relentless money-leeches.The book was also misogynistic - all the women in the book seem to fit into these stereotypes of having Barbie-jobs. As far as they and the author are concerned, the main thing they bring to the "data science" table, as a woman, is an eye for fashion, good taste in clothing, or experience trying on dresses. The tech industry already has an atrocious record in this department, and this book does absolutely nothing to help.Quite frankly I was left feeling disgusted and sorely disappointed by this book and its picture of "data science."The following quote pretty much sums up the whole book:"It’s been great being the first woman on the analytics team, as I have some inside knowledge of how I would go about finding a dress and what the effort entails... On a personal note, I’m really excited by the idea of finding more women like me—almost like my body and taste doppelgängers. My new idea is that we should be able to provide that because, once we can do that, it’s nice to know that there are other women out there who face the same issues with finding the right dress."

This was pretty well done. Naturally, a book of interviews of people in the same field will have some repetition, but that was ok. It really brought home some points, for examle the predominance of R and Python, at least at the time the book was done. It is kind of funny, how much deep thinking and intelligence goes into efforts to sell us trinkets, though. That's modern capitalism, I guess. For the record, I am a statistician. I suppose that makes me a data scientist of a sort.

This is a very good book to learn about the day-to-day life of data scientists, seen from the eyes of data science leaders at some of the leading companies such as FaceBook, LlinkedIn, and others. The interviews are very well done, asking a comprehensive set of questions consistently. The answers are long, nice and revealing of new ideas about how these leaders approach their work every day. Some of the interviewees are from M&A practitioners in this space, and don't necessarily belong in this collection. But overall this book is worth the money!

Found it a good read. You can find the full review here [...]

Excellent book. It was fascinating to learn how the great minds bebind of our most popular Internet sites evolved and are affecting our future.The time of the innocent cllick is gone. Now I know that whatever I do or click in the Internet will be registered, analyzed, and will influence policy.

The author definitely did his job with interviewing these data scientists. Their work is thoroughly discussed along with applications and inspiration. Its a great read to find out more about this new field of study

The book itself is fairly well written in that there is a consistent layout and theme, the reading is clear and easy to follow. I came into this thinking the interviews would have a little more technical value. Detailed examples, specifics on methods, that sort of thing. It reads much more like an article on LinkedIn by someone who is very aware of the legal department of every company they can name, and knows they have better lawyers. At this point I'm 2/3 through the book and I doubt I will finish it, data science contains a big element of time management and this book cannot convince me to sacrifice that time.Note: If you want a nerdy coffee table book, or are a teenager wondering if you want to get into this field, ignore everything I said because this book is for you.

There is this idea floating around “standing on the shoulders of giants”. If you are interested in data science, where it came from and where it’s going, this is a great read coming from the mouths of giants in the industry.I read this now (2018) and although 4 years passed since this books publication, the content is still relevant. It’s also cool to see how some of the predictions these people had about the future and direction of the industry has come true.Spare yourself if you are looking for some cutting edge technical piece.