Every day we hear about more and more jobs disappearing, yet the data science community cannot keep up with unprecedented demand. When you consider the growth of this industry, it’s not surprising to hear there will be a shortage of 1.5 million analysts capable of analyzing big data in the U.S. alone, by 2018, according to McKinsey. Globally, demand for data scientists is projected to exceed supply by more than 50 percent by 2018.
So why aren’t more women entering the field? It appears women are deterred from jobs in data science for the same reason they are deterred from other STEM fields. But interestingly, some stereotypically female traits are exactly the qualities that make for a successful data scientist. In fact, we’re seeing some women channel these stereotypes to move ahead of their male counterparts in the industry.
Consider the following three examples:
Collaboration. Women are skilled collaborators, able to work well with many different people. This is an important quality for data science professionals, as cross-departmental collaboration is key. Data science touches every function in a modern business, and those who are most successful are able to collaborate with all different teams and individuals.
Communication. For the same reasons, data scientists shouldt also be strong communicators. Communication is an area where many women traditionally excel, and it’s an important skill. Not only do data scientists lead dialogue and share insights among various departments, they also need to be able to listen well and speak the language of different teams. For example, communicating with the sales department may be different from communicating with the IT department. Good data scientists are able to speak to everyone.
Perspective. Being able to inspire a team and see the big picture are both important. A data scientist must be able to not only collect and analyze data, but also draw meaningful insights and understand what the data means for the company. The ability to holistically view a situation is a competitive differentiator for organizations as well as a positive attribute that many women possess.
Once we begin associating a variety of skills with data science, the perceptions of our industry can change. According to The Washington Post, women now make up 40 percent of graduates with degrees in statistics – a common starting point for a career in data science.
While a degree in mathematics is a great place to start, it’s important not to categorize the position as being completely scientific, technical, and suited only for individuals who excel at math and science. A career in data science is transferable across all industries. Whether you have a passion for healthcare, retail, or some other industry, there is likely a data science opportunity for you.
Personally, I was drawn to data science because of my love for innovation and my passion for wanting to make the world a better place through technology. Specifically, the Internet of Things (IoT) is a technology I believe can change the world. I was taken by the idea that through data science we can accelerate the impact of IoT, as data scientists are key in helping organizations get a true ROI. Additionally, Big Data can only be managed through intelligent systems and processes, which require data scientists to administer.
So how can you get started? To educate people in other fields about data science, boot camps are popping up around the world. These 10-12 week courses are a great way for people to “get their feet wet” and decide whether a career in data science is right for them, and to simply gain a better understanding of what the job entails. Further, an increasing number of universities are adding full-time data science majors to their roster of undergraduate offerings. The University of Cambridge has even created the Cambridge Big Data Strategic Research Initiative to bring together researchers from across the university to address challenges presented by our access to unprecedented volumes of data.
In the field of data science, the numbers don’t lie. While there are still disproportionately fewer female data scientists than male, the employment demands and signs from academia are encouraging. We may have to fight a little harder to break down the stereotypes that have prevented women from entering STEM fields for many years, but it’s worth the fight. Setting the stage now will inspire future generations to see that they too can be a data scientist.
For more on women in data science, see Inspiring Women As Future Data Scientists And Supporting The UN’s Global Goal For Gender Equality.
This post first appeared on VentureBeat.