Want to work in data? Here are 6 skills you’ll need

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There are many reasons someone might choose to work in data. There’s huge variety in the field, with roles spanning analytics, mining and compliance, for example. It also offers a wide salary range; according to Glassdoor, analysts typically earn around €35,000 while senior data scientists can earn up to €73,000 each year.

But what are employers in the industry looking for right now? We asked some people in the Siliconrepublic.com community to share their thoughts on the skills in high demand.


Coding is an essential part of any data job. This doesn’t necessarily narrow it down, however, as there are hundreds of programming languages to choose from.

Click here to check out the top sci-tech employers hiring right now.

Python is one of the most popular and reliable languages to learn. At Aon, employees draw on Python to help companies mitigate against possible risks and inform future decisions. According to Fergal Collins, CEO of the Aon Centre for Innovation and Analytics (ACIA), Python is a key skill when it comes to delivering impactful analytics from data.

“Its accessibility and ease of use, which facilitates rapid exploration of data to deliver analytics that solve client problems, is what makes it stand out from the crowd,” Collins said. “Python is very versatile and flexible, lending itself not only to data analytics but to web development and the ability to deploy code to many environments – from local to cloud.

“The active and supportive community driving solutions and research in Python goes a long way to making Python my team’s go-to choice of skill when it comes to working effectively with data.”

Other coding languages to think about include TensorFlow, Keras and Spacy, which Liberty IT’s Brian O’Halloran employs on a daily basis. He mainly works on natural language programming and most of his development tasks are done “knee-deep” in these languages.


 Late last year, Hays’ global head of technology, James Milligan, highlighted the ongoing demand for data-visualisation skills. Visualising data involves taking the numbers, extracting trends from them – such as potential opportunities and risks – and presenting this information in an “easily digestible way” to stakeholders, he said.

Mark Greville, vice-president of architecture at Workhuman, agrees. He told us: “Organisations will need to embrace interactive data-visualisation tools in the future. We will be rethinking how we help our humans engage with the amazing insights, so these will become the norm.

“Being able to interact with the data in new and visually appealing ways will add another level to what’s possible.”


Milligan also emphasised the importance of data-governance skills. He said that in order to bring value to an organisation, data should have “integrity and insight”.

To assess this, data professionals must investigate where the data came from, how ‘clean’ it is and how it has been analysed. Getting answers to these questions requires a worker to “critique the terminology that has been used, how information has been tagged and whether this can be interpreted with integrity”, Milligan said. “If something isn’t correct, someone needs to spot this and rectify it immediately.”

Equally important is the security measures you take with the data you’re handling. Cybersecurity professionals are in huge demand across the globe as a significant talent gap continues to widen.

We discussed the skills needed to close this gap with OffSec’s Ning Wang, who said: “Doing security well is not just following the process and going through the motions; it requires people to be able to think critically and creatively.”


Communication is massively important to almost every role and those in data are no exception. Whether you’re a data steward like Dun & Bradstreet’s Deirdre Linnane or a senior data scientist like Fidelity Investments’ Sean Curran, effective communication is key.

When Linnane first began in her role, she was surprised to learn how frequently she’d be interacting with clients. Her background in customer-facing roles helped her adjust, but she’s still careful about using too much jargon in her conversations.

For Curran, storytelling skills have proved invaluable to his work in data: “I use my technical skills on a daily basis across R, Python, SQL, maths and stats. However, I think the best skill you can learn as a data scientist is the ability to tell a story of how to approach business problems and how to come up with a solution that the client understands and trusts.”

There are other data roles that place even greater focus on the ability to communicate. As a ‘data science evangelist’, Rosaria Silipo’s goal is to help others engage with data science more deeply. She leads public presentations, lectures and courses and writes blog posts, articles and books on the topic.


Despite popular belief, working in data isn’t all about numbers. In fact, many list creativity as one of the top skills they draw on in their data role. And for Silipo, it’s one of her favourite things about working in the industry.

Setting out to solve a problem in data science is a highly creative process, she told us: “In this phase there is nothing wrong; you can let your creativity run free, experiment.”

Creativity isn’t simply a nice-to-have in today’s working world; it’s a critical skill. As Hays’ Karen Young highlights in this guest article, roles like chief innovation officer have emerged in recent years. There’s even a US consulting company, West Monroe, carving out space for all sorts of creative leadership, from chief coffee officer to chief hot sauce officer.

But whether you’re a leader or not, the importance of bringing your creative streak to the world of data can’t be overstated. “Human creativity is immune to automation,” Young said.


If you’re interested in data, chances are you’re a curious person by nature. Many data jobs share a fundamental characteristic; their goal is to arrive at answers by solving the problems presented by large amounts of information.

Marcio Melo, a senior software engineer at Asavie, once told us: “The first and probably most important trait is curiosity – wanting to know how and why things work.”

ACIA’s head of IT, Karl Heery, also believes curiosity is crucial for data workers; it’s something he looks out for in new hires across cloud engineering, IT security and more.

So if you’re determined to work in data in your career, take Silipo’s words of wisdom with you: “Keep being curious and keep learning about new technology, new algorithms, new solutions, the work of others.

“Our field is constantly changing; new uses and new techniques pop up every day. Keeping the interest and the curiosity high means to keep up with the technological evolution.”

The post Want to work in data? Here are 6 skills you’ll need appeared first on Silicon Republic.

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