How do we get more women in technology? How can the industry improve the visibility and equality of the women already in tech? Lacey Plache, VP of Data at Age of Learning, is an esteemed Data Scientist who has been pivotal in establishing and building out data teams from scratch. Based on her experiences, here are her thoughts on the gender gap in IT and six key takeaways on what it takes to be successful as women in technology:
Like many technical roles, there is a high demand for data science positions, but a low supply of highly skilled candidates to fill them. I see both genders applying without sufficient experience especially for senior positions. There are many more men who apply than women, but I have hired many talented women in data science over the years.
There are fewer women in tech because there are fewer women in STEM. Thus, I believe a large part of the issue starts with who decides to go into programs for data science to begin with. Once women get into the field, mentor-ship and even peer support in the broader community could be an issue. With the field dominated by men, especially at the senior levels, there are fewer role models for women, and it may be harder to network.
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So, I would ask: How can we get more women into technology and data science programs? How young do we have to start encouraging the right path? How can we welcome the women who do go into data science into the existing community and make them feel that they belong there?
6 Key Takeaways for Women in Technology
1. Overcome the gender gap by finding common ground.
Women need to build relationships with both male and female colleagues. However, what’s challenging about relationships is that people naturally form friendships with their same gender. As a female in tech, you are outnumbered five to one by men. If you aren’t capitalizing on these social opportunities, it makes it harder to form relationships that impact your network and collaboration.
2. Develop your networking skills.
The opportunity to take on new challenges begins with new connections. There are many studies showing women are not as good at building networks and getting mentors. A lot of women in IT think it’s good enough to do a great job to get recognized, but that’s not enough. The real impact comes from the relationships you form and how you interact with others and women don’t necessarily do as well.
3. Get a mentor.
Another big part of it is getting a mentor – someone who can give you advice and help guide you. Those are hugely important parts of your career that a lot of women in technology aren’t focused on and don’t know how to make happen. It helps you grow professionally and personally and opens opportunities you may not have encountered without guidance.
4. Take on opportunities that exceed your qualifications.
Women are less likely to apply to a job that exceeds their qualifications. People are afraid of failure or looking foolish because the unknown is scary. When considering new opportunities, think about the things that are important to you and how they align with the position at hand. What are the learning opportunities that you can have and what are the challenges? Always look for the next challenge.
5. Continue to develop your skills.
What I tell my team is to spend ten percent of their time learning new things. It may be a part of their project, research methodology, or something else that’s important. If we don’t keep growing, we fall behind. The industry is rapidly developing with new technologies and methodologies emerging that you must stay ahead of. Even if you don’t use them, it’s important to know what’s in your toolkit to evaluate your choices.
6. Be a trailblazer.
Women in tech have the opportunity to create a path and enable other women in the workplace and show girls coming out of college that if they're interested in STEM, there are several careers for them and here’s what they can do. I wouldn’t say boldly going where no woman has gone before because obviously there are women here, but it’s the opportunity - its blazing the trail.
Read Motion's article with Lacey on Data Science and Machine Learning Trends.
