As few as 15% of data scientists today are women. And that lack of diversity is a serious issue. AI algorithms are susceptible to bias, so building them requires a team that includes a wide range of views and experiences. What’s preventing more women from joining the field?

Our experience at Eskwelabs is that only around 30% of our Data Science Fellowship are women. While this is above the global average, we set out to uncover systemic issues to improve gender diversity in data science.

We reviewed results from the BCG study of STEM students on what drives their decision to pursue (or not to pursue) a career related to data science so we can examine what can be done to encourage more women into the field.

Issue #1: The STEM talent pool of women is already limited

Most STEM fields still face a daunting gender diversity problem. According to the BCG research, while women make up around 55% of university graduates globally, they account for just 35% of STEM degrees. Of these graduates, only two-thirds of them go on to a career in a STEM-related field like in engineering, analytics, or software development. This results in only 25% of the STEM workforce being women. Even fewer go on to a career in data science, with consensus across various surveys is that only about 15% to 22% of all professionals in data science–related roles are women.

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So we know that we cannot have female data scientists if we cannot attract more girls to the STEM fields to build up the pipelines needed.

Issues #2: Perception of data science is mixed amongst women

Back in October 2012, Harvard Business Review named “data scientist” as “the sexiest job of the 21st century.” Over the past decade, new job creation in the field has accelerated at a tremendous pace. However, BCG’s study showed a mixed picture of women’s perception towards data science as a career choice on two main issues: purpose and competition.

Purpose:

BGC’s study shows that the data science field is seen to be theoretical and abstract, focused on manipulating code and data with low impact and, by implication, low purpose, which disproportionately affect women:

  • Only around half of those surveyed agreed with the view that a data scientist spends his or her time solving real-life problems with high tangible impact
  • 68% of students overall subscribed to the view that data science problems are narrow and limited in scope, with little room or need for big-picture thinking.
  • While these views were shared similarly by women and men who were surveyed, the survey showed that STEM women place a higher premium on applied, impact-driven work than men do: 67% of women expressed a clear preference for such work, compared with 61% of men
  • Amongst STEM students majoring in data science or machine learning—the difference in preferences is even more clear-cut, with 73% of women and 50% of men prioritizing tangible impact in their career choice

Competition:

“Male-dominated competitive culture” topped the list of concerns about data science for many female students considering the field:

  • Averaged across countries, 81% of women (and 74% of men) pursuing a data science–related degree perceived the field as being “significantly more competitive” than other types of jobs.
  • In China, Australia, the UK, and the US, the share of women with this perception was even higher, with 91% of Chinese women pursuing a data science degree seeing high competitive pressures within the field’s work culture.

Share of students who view data science as a highly competitive field compared to other fields:

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Hackathons are intended to bring together aspiring data scientists in a fun, “let’s code together” environment—these can quickly devolve into a boiler-room atmosphere where participants feel tested and scrutinized, rather than engaged and inspired. For many people (and above all many women), these environments can be off-putting and can be a disincentive to further exploration of data science as a career option.

Issues #3: Lack of information about a data science career

The BCG study revealed that a significant share of STEM students internationally do not feel that they have a good understanding of what a “data science career” even is, what career development options it can offer, and what the day-to-day work of a data scientist entails:

  • 63% of men VS 55% of women felt adequately informed about the various career opportunities involving data science
  • 61% of men VS 55% of women understood the qualifications required for a data science role;
  • 62% of men VS 47% of women were aware of the career paths in the field

We invited Kathleen Reverente, She Loves Data Manila Chapter Lead, FTW Scholar and Julia Las, Eskwelabs Fellow and MSDS Candidate at AIM to discuss thoughts on these 3 issues uncovered from the “Women in Data” survey as well as share their own personal stories of how they came to the data field. The conversation was moderated by Carla Mumar, the CEO of SCALE. You can watch our discussion here.

How do you think we can inspire more women to become data scientists? Let us know and join in one of our future discussions.