Gender Imbalance in Data Science
With the rapid growth of data, the demand for data scientists grows as well. According to Smith Hanley Associates, data scientists are being sought for positions in a variety of fields such as healthcare, pharmaceuticals, retail, and other industries. This is great news for those interested in becoming data scientists, especially for those whose jobs were affected by COVID-19, having a secure job is important.
But there is a problem in the data science field, a gender imbalance. According to a study by Boston Consulting Group, approximately only 15% — 22% of data scientists are women and only 18% of women in the field hold leadership positions at tech companies. In this chart provided by Statista, in 2019 approximately 30% of tech jobs in the major tech companies were held by women.
In the study conducted by Boston Consulting Group, they surveyed 9,000 STEM students from ten countries in hopes to determine the cause of this gender imbalance in data science and come up with ways to have more women want a career in data science and once employed, ways to keep retention low.One way in which women may decide to steer clear of a career in data science is in their perceptions of the career. Among STEM students, a career in data science is perceived as “abstract” and “low impact”, something that does not differ between men and women. However, preferences do significantly differ between men and women, with women placing a higher preference for applied, impact-driven work compared to men. Women are more likely to not opt for a career in data science if their preferences do not align with their perceptions.
By setting clear communication of what the day-to-day job is really like of a data scientist to STEM women can help improve their perceptions of the field. Although students learn about the tools of data science in school, there isn’t much discussion of the real life examples and use cases of those tools (i.e. using regression in cancer detection problems or use of k-means clustering in identify crime localities).
Secondly, it was found that women feel that data science is competitive and non-inclusive. Approximately 81% of women who were pursuing a degree in data science believed the field to be significantly more competitive than other jobs. This may be due to companies hosting events in a “lets code together” environment which can be viewed as a test for students on their own individual abilities rather than an engaged and inspiring atmosphere. This again, can cause women to choose a different career path that will match their preferences.
These feelings of data science being non-inclusive carries over to keeping female data scientists in the field. In a study by McKinsey and Lean-In, they found that women are four times more likely than men to feel like they have fewer opportunities than men in the workplace. According to the study, women expressed feelings of being isolated/stalled stemming from “having a limited number of important or special assignments that are highly valued by high-level managers,” and “not understanding the ‘unwritten rules’ or norms of a company or department.” These feelings could be due to lack of mentorship and support for female data scientists.
A possible solution to this feeling of data science being non-inclusive and competitive in STEM students is through direct communication, whether that be through mentorship or more opportunities for internships so that female students can get a direct feel for the personalities, the way of working, and degree of collaboration. If this issue is not addressed early then it will lead to a self fulfilling prophecy.
Some other reasons that deter women from entering the data science field include the social norms that often deter women from STEM jobs. As we have seen in marketing campaigns, tv shows, and movies, an individual in tech is shown as a “geeky computer-tinkering male.”
Lack of early exposure meaning that it is common for boys to receive toys such as science sets, computer toys, and legos which are marketed towards boys. Girls take these messages from marketing, from gifts they receive from family, and messages from school life push them towards “traditional” gender roles, discouraging their interest in STEM. Early exposure to STEM and other computer-related skills can help with the gender imbalance.
In a study conducted by Harvard looking at gender gap in its computer science program, it was found that women with eight years of programming experience are as confident in their skills compared to their male peers with zero to one year of experience. Internalized stereotypes can cause women to feel they don’t have the “right” knowledge or skillset for success in the field. Mentorship in the field can have a large influence in closing the gender gap in tech and data science. In a set of interviews conducted by Women In Data, interviewees said that they had a mentor that they relied on for encouragement to remain in the field, whether a supportive family member or a co-worker open to questions.
What are the benefits of closing the gender gap?
As a woman in the tech field, I look forward to when there will be a balance of men and women in the field. With the help of male allies, companies that genuinely promote diversity and inclusion, and stronger female role models in data science and STEM, the data science and tech industry as a whole can be more successful.
Thank you for reading :)
