Women in Data Science: Changing the Rules of The Game

Half of the world’s potential data science talent is senselessly excluded as females are implicitly (and often explicitly) steered away from data science careers. This vast structural constraint significantly impedes efforts to scale enterprise data science programs to the next level. Many algorithms have been shown to be compromised by male bias. As nearly all data scientists are men, male thinking inevitably shapes the systems they create.

At the same time, the skills required to be a successful data scientist – critical thinking, structured approach, creativity, intuition, and big picture business view, are all gender-neutral. Then why do we go on limiting the scope of this strategically vital talent pool?

"I believe in disproportionately pushing for women. I push hiring managers to find women who fit the role. They’re out there. We need to work harder to recruit them." Ramyani Basu, Kearney Partner and UK lead for the Digital Transformation Practice

Key Highlights of the white paper

Children are conditioned to associate certain traits as being masculine or feminine. To break free, we much fully accept that we are all subconsciously shaped by gender bias

Students are often introduced to data science in theoretical terms that lack a practical base and fail to convey what a powerful force data science is in the real world. This perception is reinforced by the image data science typically projects ― for example, by promoting hackathons, which represent but a slice of what data scientists do

Companies understandably favor candidates who already possess the basic technical skills required for the job. However, this filtering process drastically reduces the scope of potential recruits, particularly the already limited number of female applicants.

Conclusion

The Data Science industry will be worth USD 140.9B by 2024, and we need women to play a much bigger part in shaping the future of the field. In many ways, this is a perfect match.

“Women have great analytical capabilities, even if the world does not see it that way. We need to open more doors for women." Katherine Black, Partner in Kearney’s Consumer and Retail Practice

Data science needs women’s skills, insights, and perspectives. And data science careers often allow for flexibility in working style, which should appeal to women at all stages of life, including those who want to split their focus equally between home and profession.