How can women break into a career in data?

Article by Caroline Carruthers, CEO Carruthers and Jackson 

At DataTalks last year, an annual event which brings together hundreds of data professionals from all over the world and a range of different industries, someone came up to me to say how incredible it was that there were so many women giving keynote speeches.

It’s normal in the tech world to think of STEM careers as inaccessible to women and girls and, whilst there’s still a lot of work to do in the tech space, the world of data seems to be a bit of an outlier.

It’s normal for events like DataTalks to have a large number of women giving keynotes and, as someone who’s proud to have helped to foster a wide-reaching data community, I’m constantly amazed at how far we’ve come in the data sector since I began my career. But why is data seen as a much more welcoming, and much more accessible for women than many other areas in the tech space?

I think the number one reason is because there are so many different routes into the data profession. Unlike many STEM careers, you don’t necessarily need a tech or science background: the data community values the skills brought by those with backgrounds in the arts or the business world just as much as they value those with science or more technical skills.

That doesn’t mean there are no entry requirements to a career in data, of course, but the key characteristic that defines whether someone is a good fit for a data role is one that doesn’t have a bias toward one gender or the other: curiosity. You can teach anybody about the technical side of data science or the importance of data governance, but you can’t teach curiosity, and that’s the making of a great data professional.

So, if you’re a curious person interested in a career in data, the only real barrier is self-imposed limitations. Whenever I go into schools to talk to young women who are interested in a career in STEM, I always tell them that the worst mistake they can make is to limit themselves based on someone else’s preconception of what they should be doing. Even as adults, we often self-impose limitations; we need to learn to challenge ourselves and to stop asking ”why?” and start asking “why not?”.

Data is an incredible, rewarding profession which allows you to work with the foundation of pretty much all of the technology and digitalisation that we take for granted in the world today, and all of the innovation that the world is working toward in fields such as AI and machine learning. If you’re a woman looking to break into what I consider to be the most exciting area of the tech space, you just need two things: curiosity, and the ability to ask yourself “why not?”