There’s no doubt about it: data science is THE field to be in if you are good with mathematics, statistics, programming, and have some business acumen. I’m sure you’ve seen some of the headlines trumpeting this hot new field. But in spite of the heavy demand, there’s a problem that beginning data scientists quickly discover: it’s very difficult to break into the field! I wanted to break into the field not so long ago myself. I could see the industry taking off and I didn’t want to be left behind. I had worked for years as a mathematician for a small defense contractor on problems that never really made a difference in the world and I wanted to change that—desperately. But I had never really conducted a real job search before. Sure, I had a previous job, but they hired me right out of school. And that was in 1997—well before LinkedIn. I was not having any luck even getting interviews. And I had a real wake-up call when a recruiter who specialized in placing analytic specialists told me flatly that I was “unemployable”! Clearly, I was doing something wrong in how I was presenting myself to recruiters. So I started developing strategies that would allow me to break into data science. I shifted my focus from taking endless courses online to learning how one should conduct a job search. I learned how to create a great resume. I learned how to use LinkedIn effectively. And a lot more.
Seven Keys To Success
I read books on job searches. I read blog posts. And I did a lot of trial and error to figure out what worked and what didn’t. And here’s what I discovered:
You need to develop a strategy
When most people start a job search their first thought is “I need to update my resume”. Turns out, that’s not where you need to start. You see, creating a resume, LinkedIn profile, etc. are examples of tactics. And while these are important, they won’t do much good until you can answer for yourself tough questions such as why should someone hire you, what is the story behind your resume, and what kind of job do you really want.
You don’t need to know all that much data science to get hired
This shocks a lot of beginning data scientists. So many spend countless hours taking course after course, book after book feeling that if they know every machine learning technique out there that this will magically win them a job. You don’t need to have tremendous breadth of knowledge, BUT you do need to know the basics well. It’s really a matter of knowing what data science you need to know (and it’s more than machine learning techniques)
Your resume should be a concise summary, not a collection of everything you can think of
Your resume is a critical document in your job search, but the reality is that recruiters will typically only spend a few seconds scanning your resume before deciding whether to give you a chance or not. Considering how much time and effort you put into this document, that probably doesn’t seem fair. But it is the truth. The key is knowing what exactly to put in it.
Your LinkedIn profile is even more important than your resume
Another shocker, although it makes sense when you think about it. Recruiters are desperate to fill data science positions and do a lot of searches on this social media platform. If your resume isn’t optimized to show up in these searches, no one will ever know of your existence. Once I learned how to do this, I’ve never had to send out a resume without being asked by a recruiter first. This is huge! If you haven’t already downloaded your free copy of my 17-page report on getting a great data science LinkedIn profile, make sure to do so on the right-hand side of this web page.
You need to have a story that explains who you are and what you’ve done
Because data science is such a technical field, it’s easy to ignore things like this. But what you need to understand is that in the end companies hire people, not skills. I have to thank that recruiter Annemarie for telling me “You’re going to have to come up with some kind of story to convince companies to hire someone with no experience.” Boy, was she right. With some work, I figured out ways to create an incredible story that made me a fascinating candidate.
You’ve got to prepare in order to do well on those take-home problem sets
The toughest part of these tests is not knowing enough machine learning techniques, but being able to do data preparation and munging in a very limited timeframe. That demands that you practice so when the clock starts, you can breeze through the most difficult part of these tests and get to the fun modeling stuff.
Interviews should be two-way conversations, not inquisitions
Most of the time, we think of interviews as someone grilling us by asking questions and us answering them as best as we can. And that’s certainly part of it. But equally important are the questions that you ask the interviewer! Even if you answer all the questions correctly, you aren’t going to stand out unless you ask great questions as well.
Job Hunting Is A Skill That Can Be Acquired
For those beginning data scientists out there that are becoming frustrated with trying to get that first job and not having any success, I sympathize with you. I was there myself not all that long ago. But you’ll have to do what I had to: learn how to conduct an effective job search. Once you learn the skills, you may even find looking for a job to be a fun experience! Yes, I’m sure that seems hard to believe right now. Simply learning a bunch of machine learning algorithms and taking a few Coursera courses isn’t enough to get hired with so much competition out there. Remember, it’s not how much you know, it’s how much you can demonstrate that you know. You may be quite skilled at data science, but if you don’t have a good LinkedIn profile, you have poor interviewing skills, and you can’t do well in the pressure situation of a timed take-home problem set, you simply won’t get hired. One of the best ways to learn these crucial skills is to sign up for my mailing list by entering your email address in the box on the right-hand side of this website. You’ll immediately get the report on getting a great LinkedIn profile. But you’ll also get additional tips every couple of days. Keep at it! The need for data scientists is only going to increase with time and the job (and benefits) are exceptional. Nothing worthwhile comes without effort so keep following this blog and my emails so you can master the job hunt process and get the job of your dreams.