SDS 038: How to get a job in Data Science

Very often I get asked the question, “How do I get a job in data science?” And the same applies for a job in machine learning, a job in deep learning, a job in artificial intelligence, and all of these fields interconnected which are all about data, how do I get a job in that space? Especially if I don’t have any experience? A lot of the time, people come up to me and say, “Hey Kirill, I’ve done a lot of your courses. I’ve learned a lot, but at the same time, I’m just graduating college, or maybe I’m trying to switch careers and coming from a completely different industry. How do I pitch myself, pitch my skills, to potential employers? How do I find those jobs? How do I get invited to interviews? How do I get those jobs that I want?”

And so the key thing here is the jobs that you want. So a lot of the time, people don’t even say that. People say, “How do I get a job in data science?” And that’s a whole incorrect mentality. If you’re just looking for a job in data science, just because you’ve heard that it pays well, or maybe even just because you’re passionate about the field and you’re just looking for any type of job, you probably won’t find exactly what you’re going to be happy with ultimately. You might find something you’ll settle for, but what’s the point of settling if it’s such a space where you can find the ultimate job that you’re looking for, that will make you happy? That’s what you should be aiming for.

So first of all, that’s a frame of mind you should be in. You shouldn’t be looking for a job in data science, you should be looking for THE job in data science for you that will make you happy. Because it’s not just about the employer being happy with your work, it’s also about you being happy with the work that you’re doing. And to answer the question, what I wanted to do was resonate with what we’ve been seeing our guests, or what we’ve been hearing our guests say on the podcast for the past three episodes. So the past three episodes, I’m just going to remind you of who we had on.

We’ve had Josh Coulson from LinkedIn, Senior Insights Manager for Asia Pacific there, so he’s got a huge exposure to the hiring process from both ends, so he’s seen everything. And if you haven’t listened to that episode, definitely check it out. Then we’ve we had David Venturi, who is a data science course critic, and he knows everything, or has done so much in the space of learning data science and machine learning and other things. So again, a great podcast to listen to. And we’ve just had Harpreet Singh, who is the CEO or Co-CEO of Experfy, an online marketplace for data science. So another whole perspective or lens on the whole jobs in data science situation.

And so all of them, in one way or another, what they have said sums up to the following: that you need to build an agenda for yourself. You need to create a name, a reputation for yourself in the industry in order to find the ultimate job that you’re looking for, in order to find the job that you want, that you’re going to be happy with. It’s one thing going up to recruiters and employers and just showing them that you have the skills, maybe even experience, expertise, and knowledge that is required in certain positions. It’s a whole different level when you have just shown the world that you have this knowledge, skills, expertise, and experience.

Then, what happens is you don’t have to go to recruiters any more. The recruiters are going to come to you. They’ll be knocking on your doors. Because data science is exploding. Data science is a huge field. Machine learning, deep learning, all these are fields area growing so rapidly. If other fields are declining because automation is reducing the number of jobs available, well guess what. Data science: machine learning, deep learning, and other fields like that in data are consuming a lot of the open space that is being created. You need those jobs in order to power that dimension, in order to create those tools and power those machines.

So the space is exploding, the space is growing. And recruiters are looking for talented people. All you have to do is show that you are a talented person and then recruiters will come knocking on your door. That’s exactly my advice to you, and that’s the advice I am giving everybody that make sure you’re building that brand for yourself, online brand of you as a data scientist, or machine learning expert, or deep learning expert, whoever you want to become. And how do you do it? Well as our guests on the podcast have mentioned, there are so many ways to do it. You publish articles on LinkedIn about things that you like. You start a blog. You do a few Kaggle competitions. You submit gits to github. You look into Experfy and other platforms where you can do freelance opportunities. Of course you upgrade — not upgrade, but you really polish out your LinkedIn profile. That’s step number one. If you haven’t polished out your LinkedIn profile, pause the podcast right now and go polish up your LinkedIn profile.

So there are so many ways you can build an agenda for yourself. And if you’re not doing that, then people won’t see you. And you want people to see you, to want to invite you, to want to learn more about you, to give you the offers that you’re looking for. So you want to be in a position where you have the choice of where you want to work. So it’s very, very important.

And I’m going to finish off today by giving you a quick teaser of what’s to come. So next week we’ve got a super special guest, we’ve got a returning guest, Ruben Kogel, six months after his very first episode, after 10,000 downloads of his episode. He’s coming back to tell us about what he’s been up to, and in that episode, he’s again going to talk about very similar concepts and notions about hiring, about getting jobs in data science, about the skills that you need to have. And moreover, you’ll be excited to know that Ruben is actually hiring data scientists right now in the San Francisco Oakland area. So if you’re anywhere in the Bay Area, make sure to check out the upcoming episode next week because this could be your chance to get a super cool job in data science with Ruben Kogel.

Can’t wait to see you next time, and until then, happy analyzing.