The Gender Gap in Data Science: Where are the Women?

Data science is the hottest field to work in right now. We are generating data at an unprecedented pace that is only going to increase in the coming years. This has put the field of data science, and the role of a data scientist, right in the spotlight.

While the overall gender gap in the professional world is getting closer, that isn’t the story. Not yet, anyway. Industry estimates put the share of men in data science leadership and technical roles at almost 80%.

Jobs in this field are skyrocketing right now but women are still highly under-represented. Why is this happening? What can we do to get equal women representation in data science?

Lack of Interest in STEM from Childhood

STEM, which stands for Science, Technology, ENgineering, and Mathematics, has been a notoriously difficult field for women. The majority of women struggle to land and retain a role in STEM fields.

Data science, of course, is now a key part of the STEM system.

A recent study by Microsoft revealed that women tend to lose interest in STEM from an early age. The reasons are multifold - from peer pressure to a lack of role models and support from parents as well as teachers, to a general misperception of what STEM careers look like in the real world.

Lack of Mentorship for Women in Data Science

Mentorship comes in many forms - early in school, from your thesis adviser, from your first professional boss, etc. Everyone needs support and an injection of confidence, especially when the field is as challenging as data science.

Unfortunately, women are actively discouraged in developing countries to not pursue STEM fields, and that impacts data science directly. While there are some inspiring examples in the global industry, from Coursera’s Emily Glassberg Sands to Dr. Jeannette Wing at Columbia University, India is still a long way behind in terms of promoting women in data science roles, especially leadership ones.

Workplace Culture

This is a big issue in technology that extends to data science. Coding is still considered a very male-dominant space with women, again, severely under-represented.

Whether that’s because of the organization’s culture, the aura around data science, or just the impression women get, it’s a fact that fewer women are applying for data science jobs.

So, how can this gender gap in data science be addressed?

The big question - how can we bridge the gap from where we are right now to the opportunities in data science? Here are a few suggestions:

• First, the obvious step - we should encourage young girls to take interest in STEM and nurture their education. Girls who are encouraged by their parents are twice as likely to stay in STEM, according to Microsoft’s study
• The STEM curriculum can definitely be improved, especially in India, to make girls feel more inclusive and engaged in this field
• Increase the number of role models in this field! Women should be put front and center by organizations to promote and encourage gender inclusive behavior and employment. We should celebrate the success stories of these women
• Organizations should create a more inclusive workplace culture that encourages women to participate in the projects

Final Thoughts

Let’s not forget that this field is still a very nascent field. Everyone is just getting to grips with the incredible data-driven revolution around us and it will take time for things to settle down.

There is a lot of time for women to break into this field and make a mark. In fact, it’s already happening around the globe! We can look to leading luminaries like Rachel Thomas, Vivian Zhang, Monica Rogati, Elena Grewal, Caitlin Smallwood, Jana Eggers, Daphne Koller and others who are shining the light for potential women data science professionals.

The opportunities for women in data science are going to exponentially increase in 2020 and beyond - both in technical as well as leadership roles.

• Kunal Jain, Founder & CEO, Analytics Vidhya