Want to be a data scientist? Do these 4 things, according to business leaders

Data scientists are in such high demand that the role has been described by Harvard Business Review as “the sexiest job of the twenty-first century.”

In an age of artificial intelligence (AI) and machine learning (ML), people who can help businesses collect, analyze, and interpret data are in huge demand, with the US Bureau of Labor Statistics expecting 35% growth in data scientist jobs through 2032.

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So, what areas should you focus on if you want to become a successful data scientist? Four business leaders tell us where you should focus your attention.

1. Be curious about new tech

Thierry Martin, senior manager for data and analytics strategy at Toyota Motors Europe, says the key characteristic that defines a successful next-generation data scientist is curiosity, especially for emerging technologies, such as AI and ML.

“You have to try new tech continuously,” he says. “Don’t hesitate to use generative AI to help you complete your job. Now, you can write code by saying to a model, ‘Okay, write me something that does this.’ So, be open — embrace the tech. I think that’s important.”

Martin says that he’s not your typical chief data officer (CDO). Rather than just focusing on leadership concerns, he still gets his hands dirty with code — and he advises up-and-coming data talent to do the same.

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“It’s important if you want to get ahead that you understand what you’re doing and that you’re playing with tech,” he says. “It gives me an edge, especially in mathematics and data science. I know about statistics, and I can build models myself.”

Martin says data professionals are likely to work across a gamut of technological areas. From architecture and governance to data warehouses and onto ML models and AI-powered chatbots, it’s crucial young professionals who want to move into data are technology-driven.

He also implores people who want to be next-generation data scientists to have fun and engage with the challenges they encounter: “Prototype as much as possible. And communicate with people. You must transmit your enthusiasm and knowledge to others.”

2. Develop a flexible attitude

Caroline Carruthers, CEO at consultancy Carruthers and Jackson, is another business leader who says data scientists need a blend of technical and people skills.

She’s keen to see more enterprises move from a single-minded focus on science, technology, engineering, and mathematics (STEM) to STEAM, where the ‘A’ stands for arts, and where businesses ensure data professionals have soft skills that complement their technical abilities.

“I think we have a picture in our heads of a data scientist and these specialists reside in geeky ivory towers. But businesses need the well-rounded individual,” says Carruthers. “The best data scientists understand psychology. They have a creative background and they’re open to experimentation, flexibility, and agility.”

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Carruthers, who is a former CDO at infrastructure specialist Network Rail, says job descriptions for data scientists today are much more focused on the ability to understand the business environment through emotional intelligence.

“That’s a phrase I hear so much, and I attribute that aptitude more to the artistic temperament than the scientific one,” she says. Carruthers also says data skills should be an enterprise-wide capability and not just the preserve of data scientists.

Her firm’s recently released Data Maturity Index reports almost two-thirds (61%) of data leaders say most or all employees at their organization are not data literate. “When I talk about data literacy skills, I’m talking about people right across the organization being able to use information,” she says.

3. Hone your people skills

Andy Moore, chief data officer at Bentley Motors, says your success as a next-generation data scientist is likely to come back to one key element: People skills.

“While we can talk about math expertise, which is important because you need some level of academic capability, I think more important than that, certainly when I’m recruiting, is that I’m looking for the rounded individual,” he says. “The straight A-grade student is great, but that person might not always be the best fit, because they’ve got to manage their time, they need to interact with the business, and they need to go and talk with stakeholders from across the business.”

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Certain tasks, such as visualization and user experience design, will require data specialists to step beyond the numbers and work closely with peers in other departments. Moore explained to ZDNET last year how he runs a pioneering apprenticeship program to attract next-generation data talent — and people skills are key to that initiative.

“One of my apprentices had a very memorable twenty-first birthday because they had to dial in and present their work to the board. Our apprentices get exposure at all levels of the business, so they need to be able to communicate,” he says. “So, I look for someone who will be able to interact with customers and, most importantly, take ownership of their journey. Some of our apprentices have presented at global tech conferences, so there are opportunities for them to build their personal brand as well.”

4. Stay open to new opportunities

Bev White, CEO at recruiter Nash Squared, is another business leader who recognizes the power of apprenticeship programs for younger data talent.

“Those schemes bang the door wide open to people who are not just the usual suspects,” she says. “For many people, it’s still seen as quite privileged to go to university.”

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Her organization has worked with the UK government’s Department for Education to create a new cybersecurity qualification. White hopes the qualification, which is known as a T Level and combines classroom and on-the-job learning, will encourage more young people to consider a career in digital and data.

“I’m a massive fan of apprenticeships,” she says. “These openings provide a great way for young people to go into the IT industry and find out a path that’s good for them.”

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However, White also says it’s vital to recognize that becoming a next-generation data scientist doesn’t have to be something you decide at the start of your career.

“I’ve met so many people who hate their jobs, but don’t know how to get out there and do something else. Remember there’s always different pathways you can take,” she says. “So, if you’re already in tech, fantastic. Talk to your CIO and HR team and ask them how you could move perhaps into something like data science or technical architecture, which is in massive demand.”