Data scientists are in such high demand that the role is described by the Harvard Business Review as “the sexiest job of the twenty-first century.”
In the age of artificial intelligence (AI) and machine learning (ML), people who can help businesses collect, analyze and interpret data are in high demand. So what are the areas you need to focus on if you want to become a successful data scientist? Four business leaders tell us what you should be doing.
1. Be curious about new technologies
Thierry Martin, senior manager for data and analytics strategy at Toyota Motors Europe, says the key characteristic that defines a successful data scientist is curiosity, particularly for emerging technologies, such as AI and ML.
“You have to try new technologies all the time,” he explains. “Feel free to use generative AI to help you get your job done. Today, you can write code by saying to a model, ‘Okay, write me something that does this. So you have to be open, accept technology. I think it’s important.”
Mr. Martin says he is not a CDO (Chief Data Officer) like the others. Rather than focusing on leadership issues, he continues to get his hands dirty with code – and he advises others to do the same. “If you want to progress, you have to understand what you’re doing and play with technology,” he says. “This gives me an advantage, especially in mathematics and data science. I know statistics and I can build models myself.”
According to Martin, data professionals are likely to work across a range of technology fields. From architecture and governance to data warehouses, ML models and AI chatbots, it’s essential that young professionals who want to move into data think about technology.
He also says that those who want to become data scientists need to have fun and engage with the challenges they encounter: “Prototype as much as possible. And communicate with people. You need to pass on your enthusiasm and knowledge to others. ”
2. Develop a flexible attitude
Caroline Carruthers, CEO of consultancy Carruthers and Jackson, says data scientists need to combine technical and people skills.
“I think we have an image in our minds of a data scientist in an ivory tower. But companies need a well-rounded individual,” says Carruthers. “The best data scientists understand psychology. They have a creative background and are open to experimentation, flexibility and agility.”
Mr Carruthers, who was CDO at infrastructure specialist Network Rail, says job descriptions for data scientists today are much more geared towards understanding the business environment through emotional intelligence.
“I attribute this aptitude more to artistic temperament than to scientific temperament,” she says. Carruthers also believes that data skills should be applied across the business and not just the preserve of data scientists.
His company’s recently released Data Maturity Index indicates that nearly two-thirds (61%) of data leaders say most or all employees in their organization lack data skills. “When I talk about data skills, I’m talking about people across the organization who are able to use information,” she says.
3. Hone your people skills
Andy Moore, chief data officer at Bentley Motors, says your success as a data scientist will likely come down to one key element: People skills.
“While we can talk about math skills, which is important because you need a certain level of academic ability, I think what’s more important, at least when I’m recruiting, is that I’m looking for a balanced person,” he said.
Some tasks, such as visualization and user experience design, will require data scientists to go beyond the numbers and work closely with their counterparts in other departments.
“One of my apprentices celebrated his twenty-first birthday in a memorable way because he had to go online and present his work to the board of directors. Our apprentices are exposed to all levels of the company, so they must be able to communicate,” he explains. “So I’m looking 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 technology conferences, which gives them the opportunity to develop their brand image.
4. Stay open to new opportunities
Bev White, CEO of recruiter Nash Squared, recognizes the power of apprenticeship programs for young data talent. “These programs open the door wide to people who do not have the usual curriculum,” she explains.
“I’m a big believer in learning,” she says. “These openings are a great way for young people to enter the IT sector and find the path that’s right for them.”
However, White also believes it’s critical to recognize that becoming a 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 job, but don’t know how to go about doing something else. Remember, you can always take different paths,” she says. “If you already work in technology, that’s fantastic. Talk to your CIO and HR team and ask them how you could maybe move into something like data science or technical architecture, which are the subject of massive demand.”
Source: “ZDNet.com”