The Data Science Career Guide
Introduction
At Dataquest, our goal is to help every student, regardless of their background in coding or statistics, master the skills needed to do data science and achieve the career of their dreams.
Our interactive online learning platform teaches the technical skills you need to do data science. But getting a job in data science, especially your first job in data science, isn’t always easy even when you’ve got the technical chops you need.
But before we start talking about tech skills, let's take a look at why you might want to learn data science. What kind of salary change might you see? We built a short quiz that can help you make a quick estimate:
(Not sure which role you're interested in yet? This article will help you differentiate the major roles in data science so you can make the right choice for you in the quiz below).
How could a career in data change your salary?
If you got results that looked good to you, we're here to help.
This guide exists to make the data science job hunt easier. It’s based on dozens of interviews and conversations with data science recruiters and hiring managers, working data scientists, Dataquest students who’ve gotten full-time jobs in data science, and our own internal team of data scientists and career experts.
Ready to get started? Dive right into our articles with the table of contents below, or scroll down further to learn more about this guide.
We hope that this guide offers everything you need to navigate a successful data science job search!
(If you’d like more personal guidance in your job search, our Premium subscribers have access to a special Career forum in our learning community where you can get personalized feedback, resume reviews, portfolio and project reviews, etc.)
Table of Contents
Click on one of the chapter titles below to be taken to the full length guide for that topic.
- Introduction and Table of Contents — You are here.
- Before You Apply: Considering Your Options
- How and Where to Find Data Science Jobs
- How to Write a Data Science Resume
- How to Create a Data Science Project Portfolio
- How to Fill in Application Forms, When to Apply, and Other Considerations
- Preparing for Job Interviews in Data Science
- Assessing and Negotiating Job Offers
More About This Guide
First and most importantly: We recommend that you read through this guide before you’re hoping to start applying for jobs.
In fact, the earlier you’re aware of some things covered in this guide (like what employers want to see in your data science projects), the earlier you can start getting those boxes checked off to strengthen your future applications.
This guide is designed to be a top-to-bottom guide to the entire data science job application process, and it’s designed to be read in order (although you can certainly skip around if you only need help in certain areas).
It’s also a living document that we will continually augment and update as the industry changes, and as we talk to additional sources and learn new things.
If you’ve applied for jobs or hired data analysts or data scientists recently and have an experience you’d like to share, please don’t hesitate to reach out. We’re always looking to add additional information to the guide if it will help data science students navigate the job search process more easily.
Credits
As mentioned above, this guide is based on dozens of interviews and informal conversations with data science recruiters and hiring managers, working data scientists, Dataquest students who’ve gotten full-time jobs in data science, and of course our own internal team of data scientists and our career counselor.
However, we want to give special mention to some individuals who set quite a bit of time aside to speak with us for formal interviews (and in many cases also answer follow-up questions). Many thanks to:
Alina Chistyakova — Lead IT Recruiter, Spice IT Recruitment
Alyssa Columbus - Data Scientist, Pacific Life
Clay McLeod — Manager of Bioinformatics Software Development, St. Jude Children’s Research Hospital
Edouard Harris — Cofounder, SharpestMinds
Ewa Zakrzewska — HR Specialist / Recruiter, Zety.com
Ganes Kesari — Co-founder & Head of Analytics, Gramener
Jamieson Vazquez — Talent Acquisition Manager, CiBo Technologies
Jeff Hall — Director of Human Resources, Kitware
Kristen Sosulski — Associate Prof., NYU Business School
Michael Hupp — Manager of Data Science and Analytics, G2 Crowd
Mike Kim — CTO, Outlier AI
Olivia Parr-Rud — CEO, OLIVIAGroup, personal site
Refael “Rafi” Zikavashvili — Co-Founder and CEO, Pramp.com
Stephanie Leuck — University Recruiting Manager, 84.51°
Stephen Yu — President and Chief Consultant, Willow Data Strategy
Additional thanks to all of the students who’ve spoken with us for our Student Success Stories. Their job search experiences and their advice for other students have also contributed quite a bit to this guide.
Data Science Career Guide Update Log
4/4/2019 - Added a short section called "Am I Ready for a Data Science Job" to the first chapter of the guide. This includes some general thoughts on how to know when you're ready to apply, as well as a short discussion of data science certificates and how they're not necessary to land a job in data science.
3/29/2019 - Career Guide launched!
8/20/2019 - Additional quotes added and table of contents updated.
9/12/2019 - Career Quiz added to ToC, additional content and links added to "Considering Your Options" chapter.
9/9/2020 - A variety of updates including updated information, salaries, etc.
