There exists a severe lack of gender diversity in the data science field, with women making up a very small percentage of data scientists finds out Harnham’sGlobal Diversity Report. We delve into the advantages that a gender balanced data science workforce can bring to the table along with how to achieve it.
Data science, or the use of large data for decision-making, may appear to be an esoteric or theoretical idea, yet it has a wide range of effects on how we live our lives. Data science has an impact on many of the modern conveniences we take for granted, such as an easy Google search and online purchasing. Organizations in the public and business sectors have started to recognise its revolutionary power during the past ten years.
However, there is a severe lack of gender diversity in the profession, with women making up a very small percentage of data scientists. The lack of women in data science threatens the value of data and the systems it supports, such as artificial intelligence (AI) and machine learning, and is not merely a problem of equality. On the other hand, encouraging more women to work in data science can help close the field's alarming gender gap and result in more complete outcomes. Although there are not enough women in the field of data science, there are a variety of resources that can help change that, such as networking opportunities and scholarships.
Statistics on Women in Data Science
When you look closely at the facts, the gender gap in data science is startling. According to a recent global diversity report from data analytics company Harnham, women make up only 20% of all data scientists, which is still the lowest percentage among the STEM-related fields studied. This percentage has increased by 4% from the previous year.
The statistics are similarly depressing, if not more so, for women in senior data science roles. According to Harnham, women are much more likely to hold entry-level positions than leadership positions, and 13% of respondents said their leadership teams lacked any female members.
The gender pay gap is also evident in compensation levels, with data science having one of the largest discrepancies, according to Harnham. The survey claims that women in data science occupations make over 20% less money than their male counterparts, possibly as a result of the disproportionate number of entry-level jobs held by women.
In a recent analysis on the subject of women in data science, the Boston Consulting Group discovered that there is also a perception issue in the industry. The study found that female STEM majors were 73% more interested than male students in careers that were thought to have a real-world impact. However, over half of those women believed that data science was less appealing as a job because it was too theoretical and abstract. That's a difficult hill to climb for an industry seeking greater equity.
The Impact of Women’s Rise in Data
Providing women with a role model has a significant impact on how seriously they take jobs in STEM subjects. Having female STEM role models increases young women's interest in STEM fields from 32% to 52%, according to a Microsoft poll. It is crucial to highlight the accomplishments of women in these sectors, as the Women in Data Science Conference has done. The gender gap among professional data scientists can be reduced by piquing women's interest in the field and encouraging more women to pursue degrees in data science.
The increase in female participation in data science has two positive effects. Firstly, since there are more women working as data scientists, there is a greater chance that other women may decide to study for and enter this profession. Additionally, and perhaps most significantly, the inclusion of more women in data science and STEM careers promotes a greater diversity of viewpoints and, in turn, results in better business and societal outcomes, producing more comprehensive data and more innovative — and inclusive — goods and services.
Reducing the Gender Gap in Data Science
No surprise, there is a striking disparity in the number of men and women in the sector. This has been influenced by a variety of elements, including the workplace culture, confidence level, lack of interest, lack of early exposure, and inherent bias.
This has been influenced by a variety of elements, including the workplace culture, confidence level, lack of interest, lack of early exposure, and inherent bias.
Although the gender gap in data science and other STEM professions is alarming, there are promising indicators that the tide is starting to shift. There are more initiatives than ever before to overcome the gender gap, including the Women in Data Science Conference and the growth of scholarships for women and other underrepresented groups. By fostering a more inclusive economy that generates more creative and useful goods and services, increasing the representation of women in data science is advantageous to everyone. Data science positions are among the most sought-after and profitable tech positions available.
Scholarships for Women in Data Science
There are numerous fellowship programmes and fellowships for women in STEM fields, particularly data science, many of which are targeted at underrepresented populations like women. These scholarships offer fantastic chances for women to enter the profession and are frequently supported by major technology and venture capital organisations. They include the following:
The ACM SIGHPC Computational & Data Science Fellowship intends to broaden the demographics of students seeking graduate degrees in data science and computational science, with a focus on women and underrepresented groups.
Women studying undergraduate or graduate degrees in data science, business analytics, statistics, computer science, or computer information systems are eligible for the $1,000 QuantHub, Women in Data Science Scholarship.
Program for Insight Data Science Fellows- This initiative, created by education company Insight and supported by a number of tech and venture capital firms, is open to graduates of data science degrees even if it is not especially targeted towards women in the field.
The Google, Women Techmakers Scholars Program awards $10,000 to deserving female undergraduate or graduate students who are majoring in computer science or a closely related subject, such as data science.
What can Organizations do to Advance Women in Data Science?
Through open days, university programmes, or tech bootcamps, businesses can collaborate with schools and universities to effectively drive the messaging in the early stages. There is a significant difference between learning in theory and putting it into practise, therefore for those who do learn data science in a classroom setting, there should be a stronger focus on finding solutions to practical issues. Companies can accomplish this by supplying educational institutions with technological challenges that allow students to apply their prior knowledge and research abilities to real-world data problems.
Not only could this pique people's interest in data science who might not have otherwise given it much thought, but it might also draw attention to some talented jobseekers for these companies.
I really hope that more businesses will take this as an opportunity to encourage younger generations, especially females, to get involved in this rewarding, fast-paced, and rapidly evolving data and AI movement early on. It is predicted that data science will experience more growth than nearly any other field by 2029.
