How to Get a Job in Data - Tips from a Hiring Manager

Coder Academy students eager to find out more about landing a job in data science were invited to a discussion with Kelcey Curtis, the data insights director at Signal Theory Inc.  

As a hiring manager, Kelcey has been responsible for some important hiring decisions in her time, and we’re thrilled to be able to share some of Kelcey’s top tips here on the blog so you can find out how to get a job in data science.  

 

Learn How to Get a Job in Data by Understanding What Hiring Managers Really Look For

 

The students were keen to find out what Kelcey looks for in candidates. It’s one thing to know about the attributes listed in a job description, but another thing entirely to understand exactly what a hiring manager is trying to gauge during an interview. 

“Contrary to a very data-driven human being, I usually have a pretty gut feel,” Kelcey laughs.

“So, of course, baseline – I make sure people have the hard skills that they need. Do you know how to use… the tool?”

Kelcey went on to explain that she isn’t particularly focused on whether or not candidates have already mastered the tools that they will be using on the job. Rather, if you want to know how to get a job in data, you should work on your ability to learn different tools as needed.

“I’m a big believer that you can use any tool once you’ve used a couple of tools.”

Kelcey listed other technical skills that will be essential for any role in data science, including the ability to clean data sets, and to identify when those data sets are reliable and of a high quality.

“So that’s what you can tell by someone’s resumé, usually. But more importantly, I think, I look for candidates that are self-starters…. I manage teams that require a fair bit of autonomy, and I want someone to be able to take a problem and think of creative ways to solve it.”

“So, I think a big component for me, as a manager, is that I have to be able to trust you. I have to be able to trust that you’re going to do things the right way, and that you’re going to be able to take a problem and think all the way through it, and critically analyse every piece of it and all of the different outcomes. And when you hit a point where you can’t do that anymore, I have to trust that you’re going to ask me for my help.”

“I think that’s the other big thing - and at the risk of being cliché - I look for people that are comfortable collaborating…” At this, Kelcey smiles and then laughs as she says, “Data people really don’t like sharing.”

“We don’t like handing off work. We like completing our own work. We like to take our data with us as we go. We’re not great at sharing. So, I like people that are comfortable collaborating, even when it’s uncomfortable for them to ask for the help.”

 

The Top Skills for Anyone Who Wants to Know How to Get a Job in Data 

 

If you are trying to figure out how to get a job in data analysis or data science, then you will need to list the right skills on your resumé, and then find a way to demonstrate that you really have that skill set in an interview setting.

To find out more, we asked Kelcey to elaborate on the top skills (both soft skills and technical skills) that she seeks in a candidate.

“The analysis skills, like I said, are baseline. I look for those. You have to have them. And it spans beyond techniques, and I kind of mentioned this earlier … you have to show me that you can learn tools. And just because you list out the entire Microsoft suite on your CV or your resumé, it doesn’t really tell me anything.

“So, one of the things that I ask in an interview is, ‘What tools have you learnt? And was it self-taught, or did someone teach you?’

“And I think there’s a big difference between being able to step through something on your own, versus someone feeding you the information.” 

Kelcey then went on to explain that for anyone who wants to know how to get a job in data science one of the most important soft skills will be storytelling.

“So, storytelling’s a big one,” Kelcey says.

“You can’t put numbers in front of people and just expect them to get it. It’s just not the way we’re wired. So, you have to be able to take data, really interpret what it means in the most pure sense of it, and develop a story from beginning to end that’s going to compel someone that the data is important.”

“The other thing about storytelling is that you have to seek it out, right? You have to seek out that skill if you don’t have it naturally. And a lot of people don’t. I don’t. I learnt”.   

 

Ongoing Learning is Key to Getting (and Keeping) a Job in Data

 

Following up on Kelcey’s earlier comments regarding the ability to learn new tools and methods continuously, one of the students in the audience was keen to find out whether Kelcey would place more value on self-taught knowledge or educator taught tools and methods.  

For anyone wanting to know how to get a job in data, and then to turn that initial job into a rewarding career, it might be interesting to know that Kelcey believes that anyone in data science should continue to gain skills and knowledge in a variety of ways.

When asked whether self-taught tools and methods carry less weight in her opinion, Kelcey says that this isn’t the case.

“I actually tend to be more impressed when I hear someone has taught themselves tools,” Kelcey says. “So, for instance… when I interviewed for the role at Signal Theory, I had never touched Tableau. It was not in my toolkit. I did, like, a free student trial before the interview because I knew that’s what they used… but they asked me about ten different tools that I’d never even heard of. And I said, ‘I have confidence that I can learn tools, and here’s my proof point - before I walked in the door, I taught myself Tableau so that I could come in here and tell you that I knew Tableau.’”

Having explained the advantages of being able to teach yourself as needed, Kelcey then went on to explain why continuing to learn from professionals in the field is important for data professionals throughout their careers.

“For instance, I’m learning R, and I’m learning it for the first time. I taught myself roughly, previously, because it was a necessity, but I’ve learnt a lot more now that someone is teaching it to me.”

Kelcey believes that both methods are essential for anyone who wants to know how to get a job in data.  But what she is looking for in candidates is more a particular quality, than a list of skills learnt.

“I think that they hold their own weight, independently, but I need to see in a candidate that they’re not afraid to approach a tool that they’ve never used before,” Kelsey says.

 

How to Get a Job in Data When You Don’t Have a Data Science Background

 

Here at Coder Academy, many of our students undertake a bootcamp because they want to make a career transition or a complete career change. In light of this, students often want to know how to get a job in data when their previous education and experience may be in a completely different role or industry

In other words, how can incoming data professionals best position themselves as strong candidates for an analytical role, especially if they don’t have a “traditional background”. 

“The non-traditional background? My advice is to leverage that,” Kelcey says. “It is really, really, critical to have teams that have diverse backgrounds because that is where the best ideas come from.

“So, I think one of the best things you can do if you’re coming from some different world, is to go to a manager and say, ‘I bring a unique perspective. I’m going to be able to provide a different lens than anyone else on your team. And I’m going to work with them to broaden their perspective.’ I mean, I think that’s a huge asset when it comes to your skill set and your experience.

“The other thing that I think is really, really, important, is to just bring passion for the work. Don’t come in and say you’re really great at doing statistics, or you’re really great at doing analysis. Tell us why you’re doing it, and why you care. Because that passion is going to take you a whole lot further than a toolbox.”  

“You can learn tools,” Kelcey says. “You can learn skills and techniques, but you can’t learn passion. You can’t. You have to find that for yourself.”      

 

How to Get a Job in Data if You Suffer from Imposter Syndrome

 

So far, Kelcey’s advice has focused on how to get a job in data by honing your skills. But what if the obstacles you face trying to get your foot in the door for a data science career actually come from inside your own head?

We decided to find out if Kelcey had ever grappled with or struggled to overcome imposter syndrome

“Overcome it?” Kelcey asks. “I haven’t overcome it! That’s still an everyday thing.”

“Imposter syndrome is this really interesting sort of thing, and I don’t know that it goes away. But what I would say, is that you’re really not an imposter, and I think that’s a big thing, that you have to remember that everything that you bring is added value.

“You rarely overcome it. You just have to show up every day - bring what you bring, and make the best of it.

“So, I have absolutely, really no solid advice on overcoming imposter syndrome. I’ve been in this profession a decade, and I’m actively learning every day – new skills, new tools, new ways of applying my learnings. So, I often feel like I’m in over my head, that I’ve taken a bigger risk than maybe I was prepared for, but I also have to lean on the fact that I have a track record of figuring it out.

“I think that’s the other thing. You kind of have to look back on your history and say, ‘You know what? I figured this out ten times before – I’m probably going to be okay.’”     

 

How to Get a Job in Data by Learning the Right Tools and Processes

 

The discussion then moved on to the specific tools and processes that students should focus on. If you’re wondering how to get a job in data, then finding out which techniques, tools, and languages hiring managers prefer is probably high on your priority list.

“If I think about specific techniques, I would say, learn, learn, learn, modelling and regression,” Kelcey says. “I mean, every type of multi-variant model you can learn - learn them all. And I can’t emphasise that enough. It is the one constant through every type of analytical work I’ve ever done.

“So, that’s a big one.”

Kelcey then moved on to tools and languages.

“I work in SPSS – that’s my preferred tool, that’s kind of what I ‘grew up on’.”

“R is not going away - so, if you’re not learning R, and you have the desire to really be tool agnostic, I would say R is a really good one.

“If you’re going to learn a language, Python is kind of it. I would also say CSS is in that list for me, just because a lot of visualisation platforms use CSS. But that’s if you really want to get into customisation,” Kelcey says.

“Those are really the big ones, and I think in terms of soft skills, because I really can’t leave those out, if you are a strong presenter, you’re going to win hearts. It’s the way up the ladder - to be a strong presenter.”  

 

Learn How to Get a Job in Data by Remaining a Student

 

As the session wrapped up, we asked Kelcey if she had a final call to action for any data professionals in training.

“I don’t know if it’s a call for action,” Kelcey says, “but it is certainly going to be a necessity - brace for change.

“It is a field that is never stagnant. It’s always going to change, and change all the time. So, be prepared to be a student forever. If this is the route you’re going, you’re going to continue learning, and if you’re not learning, then you’re becoming obsolete. 

“So, you’ve just got to keep up with the trends, with the tools, with the technology, with the applications. This industry is changing faster now than it has ever changed, and it is wild!” 

 

If you’d like to learn how to get a job in data, then why not attend a Coder Academy info session - they are a great way to hear from industry professionals like Kelcey, and to learn all about the ins and outs of our bootcamps. 

 


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