Today, many leaders believe that data is one of the most important resources for their business and that the effective use of data will determine competitiveness in the future. It is therefore not surprising that working in data science was not only voted as the best job in 2016 but has been referred to in the Harvard Business Review as the sexiest job of the 21st century. High salaries, great career opportunities and flexible working all make this an attractive field to work in. But why are there so few women?
According to the Office for National Statistics in the U.K., women account for just 13% of STEM (Science, Technology, Engineering and Mathematics) professionals. Only an estimated 9% of CIOs are female. Girls make up 46% of the students taking advanced placement calculus test, but approximately 80% of them never take a computer science class.
Is it that women simply aren’t interested in data science and technology? Are they being shut out? Why aren’t there more women in data science careers?
The “Women In Data” summit suggests five main reasons:
Women bear a heavier load balancing work and family. A Pew Research study done in 2015 showed that women are more likely to change their work hours or detour their career to take care of family than men, and more likely to say that being a working mother has a negative effect on their career advancement than working fathers. This is largely thought to be due to remaining stereotypes about gender roles and who should be responsible for family. Even when both parents work, mothers are more likely to be the ones to take off work to care for sick children, reduce their hours, and take care of more of the housework. Over time, these differences accumulate and women are disadvantaged when it comes to career advancement. And this is true for every work sector, not just STEM or data.
No clear career path. In the past, data analytics might have been a part of the marketing department, finance, or IT, and lacked any clear career progression. Generally, women tend to favor stability over opportunity for advancement, whereas men are more likely to find — or create — a path to career advancement for themselves. Women may also see tech jobs as demanding and inflexible, and not well suited to work/life balance they often cite as being important to their happiness with a job.
No female leaders or role models. Without mentors and role models, women may have difficulty picturing themselves in certain roles. This is especially true when the field is something of an “old boy’s club,” with a large majority of men. Not all women want to be trailblazers, and would prefer to follow in the footsteps of other successful women. It takes a certain personality to be willing to break glass ceilings, and it isn’t a character flaw that not all women find those sorts of challenges desirable. Research shows that a major reason women don’t enter technology fields is that they worry about being uncomfortable or unhappy working alongside the people they perceive to dominate the industry. Hopefully, as more women enter the data science fields, they will pave the way for additional women to feel comfortable pursuing data careers.
Lack of awareness. Data analytics is such a new field that many young people may not even be aware that the career is available to them. Women who excel in science and maths may choose more traditional careers in fields like finance, where the path and options are more clearly defined. Additionally, women may not understand what the field really is, and believe it’s all about statistics or coding. Research shows the number one reason women don’t go into technology is they don’t find it interesting — but that may very well be from lack of understanding and exposure.
Low confidence. Studies have shown that women and girls tend to lack confidence in science and maths, even when their results are as good as or better than the boys’. This is a systemic problem that some believe begins with the way STEM subjects are taught in schools, and which tend to favor boys’ natural self-confidence. When asked, a major reason women don’t seek technology jobs is because they believe they won’t be good at it. In addition, women in science, maths, and academia are more likely to be the victims of subtle (and overt) harassment and bullying. Anecdotally, this leads to more women opting out of these fields to pursue other careers.
In short, it doesn’t appear to me that women are naturally disinclined to be interested in a career in data sciences, but that there are many more barriers to entry for women than men, starting in their school years.
And there seems to be a sort of catch-22 happening within businesses. Martha Heller, a recruiter and author of The CIO Paradox, reports that while companies express that they would love to hire women for tech positions, women report that they are not being promoted from within.
But the lack of women is a detriment to the field of data science. I believe women have a lot to offer, and aren’t naturally a poor fit. In turn, the career paths in data also have a lot to offer for women. This has been recognised by the field and has led to conferences that focus on women and opportunities for women in data.
A data scientist has got great career prospects and the world is facing a huge shortage of qualified candidates that women could certainly help fill.
I feel that if we had more women in data science, projects would deliver better results. Creativity, intuition, and communication skills, for example, are crucial for any data science team, and tend to be soft skills that women excel at. What’s more, the actual coding and number crunching can increasingly be done by machines and automated algorithms, bypassing the need for advanced science and maths degrees; more critical is the skill of asking the right questions of the data.
On a different level, data science is a job that can be performed in a flexible setting with the ability to work from home. Because so much of the work can be done remotely, the field actually can provide excellent opportunities for women looking for a level of work/life balance, wanting to be home when the kids get home from school, etc.
We must do more in educating our young girls and supporting their interests in STEM fields, educating young women about the financial benefits and opportunities of technology careers, and dispel some of the myths of technology careers being male-dominated.
I believe data and technology are the language the world will increasingly speak in the future, and it’s a matter of needing as many talented people as possible — men and women — to join the technology workforce in order to meet the growing opportunities and demands.
And any field in which half the talent pool is being overlooked or not encouraged to reach their full potential is a field that is destined to suffer.
As always, I’d be interested in hearing your thoughts in the comments below.
You might also be interested in my new and free ebook on Big Data in Practice, which includes 3 Amazing use cases from NASA, Dominos Pizza and the NFL. You can download the ebook from here: Big Data in Practice eBook.
