Build a Career in Data Science

by Emily Robinson, Jacqueline Nolis

Build a Career in Data Science is your guide to getting your first data science job, then quickly becoming a senior employee. Industry experts Jacqueline Nolis and Emily Robinson lay out the soft skills you’ll need alongside your technical know-how in order to succeed in the field. Following their clear and simple instructions you’ll craft a resume that hiring managers will love, learn how to ace your interview, and ensure you hit the ground running in your first months at your new job. Once you’ve gotten your foot in the door, learn to thrive as a data scientist by handling high expectations, dealing with stakeholders, and managing failures. Finally, you’ll look towards the future and learn about how to join the broader data science community, leaving a job gracefully, and plotting your career path. With this book by your side you’ll have everything you need to ensure a rewarding and productive role in data science.

Genres: Programming, Nonfiction, Technology, Computer Science, Science, Computers, Coding

250 pages, Hardcover

Published January 1, 2020

Reviews

[Alex · Rating 5 out of 5]

I loved this book! Super practical advice that I was I had when I had graduated university, but I also found it entertaining and interesting to read as the authors did a great job writing it and letting their experience shine through. The additional interviews with data scientists at the end of the chapters were excellent as well.

[Alex · Rating 4 out of 5]

a clear and pragmatic read that has a lot of good advice while keeping a level head about data science and avoiding hype. as someone primarily interested in research roles, i was worried this book would not have much for me, but i pleasantly surprised, especially by chapter 2, which describe several archetypes of companies hiring data scientists, and by chapters 10 (making an effective analysis), 11 (deploying a model introduction), 12 (working with stakeholders), and 13 (when your data science project fails).

these chapters emphasized the collaborative nature of the data science as a human endeavor privy to politics, rabbit holes, uncertainty, risk, and failure. i was especially pleased by the concrete advice offered in the human-skills/cognitive portion of the book, which might be thought of as 'meta data-science.' the other portion of the books are also well written, but contain more cotidian advice that i suspect won't be quite as new to readers.

definitely a book i recommend to junior data scientists. i hope nolis and robinson author together again -- i'll certainly buy anything they write.

[Pablo Tercero · Rating 5 out of 5]

I absolutely loved this book, it's full of great advice, thought provoking ideas, career guidance, enlightening interviews, etc... As a relative new comer to the arena it has been immensely useful to read/ learn from two luminaries on how to develop a career in ds.
I'm also full of excitement on how to use their myriad of additional resources from book recommendations to blog suggestions and interview questions.
The book is an incredible resource for any aspiring / new or relatively new data scientist and I can not recommend it enough.

[Niyousha · Rating 1 out of 5]

If your knowledge is absolutely zero in data science it might help you otherwise it is just a fluffy book that is good for nothing. There are much better books in this area such as ace the data science interview that can help a lot. Also the authors seem pretty friendly and welcoming in their podcast and book but not so much in the real world. 👎🏻

[Andrés Pérez Figueroa · Rating 5 out of 5]

Me ha acompañado en mi transición desde el mundo académico a un rol de data scientist en la industria que he acometido en los últimos meses. Y cada paso que estaba dando estaba perfectamente reflejado en este libro (salvando las distancias culturales, ya que está escrito desde una perspectiva norteamericana). Desde que tipos de conocimientos adquirir/reforzar, a como buscar trabajos de data science, como afrontar las entrevistas, las negociaciones, como arrancar en las primeras semanas o como ir solucionando problemas del día a día. Es un magnífico reflejo de lo que te vas a encontrar en esas fases de tu carrera.
Muy recomendable para aquellos que quieran entrar a trabajar en un rol de datos, ya vengan de otro campo o bien estén planteando que estudios hacer.

[Harsh Darji · Rating 4 out of 5]

I really enjoyed reading this book, it brought a lot of clarity on what kind of data scientist I want to be. But I felt something was missing, I was hoping to read more about:
1. How to go about networking, finding community, and a sponsor (l am glad I found them on Emily's blog)
2. Also, I have spoken to a lot of people and they have said that getting a Machine Learning job straight out of school is very difficult. It would be awesome if the book could address some points regarding reality.

Some of my fav chapters were:
1. Data Science Companies
2. Building a Portfolio
3. Interviews after each chapter

[Lauren · Rating 5 out of 5]

I found this to be a really good reference that I’ll pick up again and again throughout my career. This book is full of current and useful advice, how-to’s and interviews with industry professionals. It contains chapters on topics ranging from data science interview/case prep to how to deploy a model into production. This isn’t a technical reference and it’s written in a conversational tone, with lists of additional resources at the end of each chapter if you want to dig in to a topic more technically or from a different angle. I think this would be a useful reference for anyone working in data science; there is something valuable in here for everyone regardless of experience level.

[Sara · Rating 5 out of 5]

This is a very good book and it definitely has helped me as a person in transition from academia to industry. However, I think some of the advices in this book are a bit outdated since we have come so far with AI in such a short time and self learning as well as productivity and the way we look at programming now has changed immensely. I wish they update the book and put some specific advice for post-chatgpt time. I gave it a 5 stars anyway because the content would have been flawless had I read it just a couple of years ago🙂

[William · Rating 5 out of 5]

A must-read for aspiring data scientists. Over the past year, I have invested countless hours in doing 1-on-1 chats with data scientists and attending relevant info sessions, and nearly all the career advice I learned from talking to data scientists can be found in this book. The book also offers so much more valuable advice on preparing, settling into, and advancing in data science roles. I plan to come back to this book periodically.

[Brandon · Rating 5 out of 5]

Very useful book to navigate the whole process of getting into this popular industry. It has a little bit of everything, but is mostly focussed on developing a stronger and more realistic understanding of the domain. It has clear explanations accompanied by excerpts from industry professionals.

It feels a bit informal, which makes everything appear less daunting to someone who doesn't know where to begin.

[Mohamed Rafeek]

This book discusses everything about the Data Science career, so it was written for beginners. I was always looking for a book like this to learn more about such a great field with high-paid salaries. Although it covers everything in detail, and I can find this very boring, it's still an amazing book to begin the Data Science career journey.

[Jie · Rating 4 out of 5]

A career guild line book covering almost all the topics to succeed in data science field....but some chapters is a little of chatterbox, had to skip some sections. Overall, it’s a good book. I hope I choose have read it one year earlier before I stepped into this area.

[Atun · Rating 5 out of 5]

I would highly recommend this book for someone who is considering and/or in data science field. It is filled with highly practical advice and interviews with top leading data scientists in the field. I am so glad that I get to read it and I hope that you find this book as insightful as I do.

[Daniel Musyoka · Rating 5 out of 5]

This book is excellent work!! For anyone looking to understand Data science, how to start career in DS and how to nevigate , how to handle interviews , switching jobs or careers etc. as well as getting into a community. Its a great piece worth reading

[Paola Prieto · Rating 4 out of 5]

Nice book! it gives a clear understanding of the Data Science field and different types of companies. The interviews with experienced DS feel relatable and practical. It might not be aimed at senior professionals, but it’s a valuable read for those starting out in data science.

[Alex Klyanchin · Rating 5 out of 5]

Realistic and pragmatic book half of which confirmed my experience and other half prepared to possible challenges.

[Nikita Bhagam · Rating 5 out of 5]

Very informative! Its a great guide to self-learning new topics in Data Science.

[Dhaval · Rating 3 out of 5]

3.5 Stars

[Seren]

Finished at the beginning of ch4. Coming later when I have enough knowledge to build a portfolio.

[Domnica · Rating 5 out of 5]

This book should be the first you read if you want to build a career in data science. The first chapters are suitable to read for any data professionals as I find the insights applicable across. Besides that, I think data and business analysts should read more about data science in order to understand the entire data lifecycle. It’s important when you are part of a team work/project, to strive to understand everyone’s contribution and effort.
The book is very well written, following a good structure throughout the chapters. I liked that after every part, the books referenced are listed which makes it very easy to dive deeper into the knowledge. In addition, in appendix interview question are given with example answers.
This book is a great guide into data science! Really recommend reading it at least once!!

[Eddie Wharton · Rating 5 out of 5]

I wish this was around when I started my career in data science 5 years ago. Very good advice for how and where to start. Even for professionals with more experience, this book is quite helpful. It gives a glimpse of different working environments and the possible data science career paths. Offers useful vocabulary and frameworks. Highly recommend!

[Joseph Arcila · Rating 3 out of 5]

As a self-taught data scientist, I didn't face any of the issues exposed in the book about choosing the self-taught path, I found well-defined paths on books and career tracks from Coursera, Datacamp and Udacity, and it was definitely not like, "Where should I start?" also, there are slack channels, and student forums from Udacity, Coursera, and Datacamp where you can get most questions answered.

[Francisco Galán · Rating 4 out of 5]

Amazing book full of useful advise.