The field of data science continues to grow quickly, and organizations of all sizes and in all industries need people who can analyze the numbers, dive into new theories, and innovate. Data scientist was the #1 job in the U.S. in 2017, but finding qualified applicants is proving to be a challenge for companies. Jobs in data require knowledge of programming, algorithms, statistics, and more ”skills that take a lot of time to develop.
Like many tech jobs, the data science industry is currently male-dominated. According to one study, 70% of data scientists are men. With the shortage of qualified candidates in the field, however, this is a great time for women to join the industry and move into these roles. Here’s why closing the data science gender gap is so important.
Women Can Excel In Data When Given the Opportunity
We’ve lived with damaging stereotypes about women in tech for decades. Although most early programmers were women, today many people hold the opinion that women aren’t good with numbers, analytics, or other STEM topics. Those false stereotypes hold women back from pursuing data careers and reinforcing the gender gap. Currently, women make up just 26% of data professionals.
Women are ambitious, skilled, and adaptable, and they can excel in data analysis roles when given the opportunity. With 1.4 million computer science positions becoming available by 2020, that opportunity may have finally come. Companies need to be willing to diversify and welcome women. This could help women leverage their talents while helping to close the gender gap and filling open positions.
Hire Data Roles with New Mindset, and Consider Women
Thanks to those harmful stereotypes, many hiring managers take their internal biases with them when looking over a woman’s resume. Too often, women’s qualifications are overlooked in favor of male candidates, which doesn’t do anyone any favors.
When hiring for data science, try to be aware of any inherent biases you may have and look at open data positions with a new mindset. Consider what candidates have done and how they have worked to develop their mind and skillset. People need more than hard skills to excel in data analysis. They also need to be creative, innovative, and able to communicate.
In addition to the basic skills needed for data analytics, look at a candidate’s personality. You want to hire someone who can take action, be passionate about what they’re doing, and have the resourcefulness to deal with inevitable challenges. People who can think differently and solve problems quickly often make the best data scientists. Women often fit that bill perfectly.
A Woman’s Career Background is What Shapes Who She Becomes
Many women have more talent and leadership ability than their resume portrays. Just navigating the business world as a woman helps to build valuable communication and leadership abilities. These soft skills may not seem important in a data science role, but they’re key for data scientists, who must explain their work to people who may not fully understand it. It’s more important to consider candidates as individuals, rather than their years of experience or education. Find out what they have achieved, what drives them, and how they think.
Give Women a Chance in with Data Jobs
Many women never get a chance to prove themselves in the field of data science. Because of a number of factors related to the gender gap, a woman may not be the most experienced candidate. However, that isn’t always the most important factor in the hiring process. Consider hiring women because they bring different and valuable skills and experiences to the table than men.
There are many fields that don’t relate directly to data science but can teach people valuable skills that transfer well to analytics. Women who have worked in marketing, PR, media, and similar fields may have developed valuable creative and analytical skills.
Time for Women to Step In
The field of data science may be dominated by men, but there’s an opportunity for women to step in. The field is growing, and it’s time to end the gender gap. Companies need to be willing to take a chance, and let women show what they can do.
