The gender gap in data sciences and how your company can close it16 Mar, 20236 Minutes
Despite the growing demand for data scientists, the field is still male-dominated with women...
Despite the growing demand for data scientists, the field is still male-dominated with women making up just 26% of the data science workforce. The gap is not only a moral concern, but it also limits the potential of the data science sector. So, how can your data science department close its gender gap?
What is the gender gap?
When it comes to the workplace, the gender gap refers to the unequal treatment and opportunities that exist between men and women in employment. You can see the gender gap manifest in a range of ways, from disparities in pay and promotions to a lack of diversity when it comes to senior leadership positions. However, despite the odds, some women have broken the barrier and worked their way to the top in the life science data science field. This includes Daphne Koller, CEO and founder of Insitro, Animashree Anandkumar, director of machine learning research at NVIDIA, and Sharvari Guija, director of bioinformatics at Genuity Science. But, while it’s exciting to see women in high positions, there is still a long way to go before the data science sector is gender balanced.
What closing the gap could do for your business
It’s been estimated that a 50% reduction in the gender gap can lead to a GDP gain of 6% by 2030, and if that’s closed in its entirety within the next 15 years, that figure can increase by an extra 6%. So, from a financial standpoint, closing the gender gap benefits organisations and the wider economy.
But it also allows for a wider range of perspectives and ideas to be brought to the table. This can result in more creative problem-solving, innovative approaches, and a better understanding of diverse customer needs, all vital when it comes to the data science industry.
A gender-diverse workforce can also enhance workplace culture, leading to greater job satisfaction, improved retention rates, and reduced turnover. And with a reported shortage of 250,000 data science professionals, ensuring you do everything possible to retain your employees is crucial. Closing the gap can also help you attract a wider talent pool, as companies that prioritise and can walk the walk when it comes to diversity, equity and inclusion are more attractive to job seekers. A gender-diverse workforce not only promotes equality and social justice, but also offers a strategic advantage in today's globalised and competitive marketplace, so making it a priority for your business is vital.
How can you work to reach gender parity in your firm?
Help encourage women to enter data science
To increase the number of women in data science, your firm could promote the field as an attractive option for women to pursue. One of the primary ways to attract more women to the field of data science is by partnering with schools and universities. By establishing relationships with institutions that encourage women to pursue STEM, you can show your commitment to addressing the issue and potentially reach a wider pool of future candidates. This can be achieved by providing mentorship, internship opportunities, and access to resources that support learning and professional development.
In addition, offering scholarships or apprenticeships within your own organisation can help to remove barriers that may prevent women from pursuing a career in data science. This not only provides opportunities for women to receive an education, but also demonstrates your company's commitment to diversity and inclusion.
Hosting workshops and events can also help to showcase the benefits of a career in data science. These events can include panel discussions, talks from industry leaders, and networking opportunities. By featuring successful women in data science, attendees can see first-hand the opportunities that are available to them and the potential for growth and success in the field.
Create and communicate an inclusive culture
Creating an inclusive culture that values diversity and encourages women to succeed is crucial for closing the gender gap in data science. This can be achieved by providing mentorship programs, promoting work-life balance, and offering flexible working arrangements. Implementing gender balance policies such as breastfeeding, menopausal, and menstrual leave is also important for creating an inclusive workplace. It’s also a good idea to ask the women of your workplace what type of additional support they’d like from you as an employer.
These actions recognise the unique challenges faced by women and provide them with the support they need to manage their health and wellbeing. As a leader you should also participate in unconscious bias training to ensure that they are treating all employees fairly; this can help to identify any harmful actions or behaviours that may be inadvertently preventing women from advancing in their careers and provide strategies for addressing these biases.
Address your own gender pay gap
In recent years, data science has emerged as a field with immense growth potential and high earning potential, but this has not translated into equitable pay for all. Women continue to face pay disparities compared to their male colleagues. For example, in the US it’s estimated that female data scientists are paid between $90,000 - $100,000, while male data scientists are paid between $100,000 - $125,000.
You should conduct regular pay audits to ensure that there is no gender pay gap, and if there is, take immediate steps to address it. Pay audits can help identify any pay gaps that exist within your organisation and help determine the root causes of these disparities. This information can then be used to develop strategies to close the gap and ensure that all employees are paid fairly for their work. This includes providing equal pay for equal work, offering transparent salary structures, and creating opportunities for women to advance to leadership roles.
Be transparent with the results of your audits and hold yourself accountable. By sharing the results of pay audits with employees and the public, you can hold yourself accountable for addressing any disparities that exist. This can help build trust and enhance the reputation of your organisation as a fair and equitable employer.
Increase female representation in leadership roles
While there has been progress in recent years, the reality is that women remain underrepresented in the data science field. This lack of representation can be discouraging for women who aspire to be in leadership roles within the field and can make it more difficult for them to envision themselves as future leaders. Therefore, to close the gender gap in your department it is crucial for women to see other women in leadership positions. Consider setting targets for female representation in leadership roles and creating career progression paths for women, taking into account some of the known barriers to progression.
Increasing female representation in leadership roles can have a positive impact on the entire department. Research has shown that companies with diverse leadership teams are 15% more likely to outperform those that are not gender-diverse, as they are more likely to consider a wider range of perspectives and ideas. By promoting gender diversity within leadership positions, your organisation can improve its overall performance and competitiveness in the market.
There has been some progress in recent years within the life science sector as a whole: a 2018 survey showed that when asked to draw a scientist more children than ever before drew a woman. While it is positive to see children’s preconceptions changing, there is a still long way to go before the sector can be viewed as gender balanced. 50% of women are leaving their tech careers by the age of 35. So, closing the gender gap in data science is not only the right thing to do, but it also makes good business sense. By attracting and retaining more women in the field, your data science department can benefit from increased diversity of thought, leading to better decision-making, problem-solving, and innovation.