Data Science training in Delhi in modern times is considered one of the most valuable fields for young professionals with a wide range of growth. Everyone is dealing with technology to some degree now. Therefore, data scientists are in high demand as they can equip firms to plan better and more effectively. However, when we look at the depths of the sector, there is a problem — a lack of gender diversity.
With more than 660 million women, India holds the top spot when it comes to the number of women graduating in science, technology, engineering, and mathematics (STEM). Women make up about 40% of Indians earning STEM degrees. But the country itself is ranked 19th when it comes to their employment, thus raising a red flag for the system, administration, and society as a whole.
Although women make up about 55 percent of the average university graduates internationally, only two-thirds of this important talent is pursuing a career in a STEM-related field such as engineering, software development, or analytics, and even fewer are pursuing a career in knowledge. science. Women make up only about 15% to 22% of all data science professionals, according to various studies from the WEF, the Global Gender Gap Report, and the BCG study.
Commenting on the first obstacle, Mathangi Sri, VP of Data Science at Gojek, said: “The importance of STEM education for girls is not emphasized in society as a whole. We still have stereotypes that put good art in the hands of girls and STEM titles in the hands of boys. Girls should be encouraged to try new things, let them try harder, and let them often fail in school. Within and outside the family, we must work hard to eradicate prejudice. ”
He added, “Some biases are natural that may arise during promotions and even in negotiations. Furthermore, it is not uncommon to see people who speak frankly and confidently progress faster than those who do not. Many women will probably fall short in later life. ”
A few other reasons can be given to this huge imbalance in the fields of data science.
First, the stamp of perfection given to the part of women in our society tempts us to prevent them from making mistakes, while the only way to learn and stay healthy in the field of data science is to make mistakes.
Second, the technology industry, with or without it, is dominated by men, which often results in fewer women role models.
Third, interestingly, the perception among women from the STEM field is not good. Readers believe the topic is more theoretical and intangible, focused on coding and data with less impact and, increasingly, less purpose. In addition, the competitive feeling of cutting and the culture of “nerdy” work among female aspirants prevents them from even entering.
The high level of profits of women in data science and AI fields can be traced back to the presence of bullying, sexism, and sexual harassment in the workplace. Women are also discouraged from continuing their data science and AI work because of the gender pay gap, poor job growth for women, male-dominated office culture, lack of access to mentors, and gender bias in hiring. Additionally, in the technology industry, extraction is a major problem. Many women in technology companies leave their jobs in the middle of their careers (10-20 years). Most of them stop or continue working in other sectors, according to industry research.
Evidence-based performance of the policy is compromised if it is based on distorted data. The fact that most data scientists — collectors, editors, analysts, and decision-makers — are men, is a potentially biased source for many data sets. Therefore, in addition to working on current challenges, in order to overcome the shortage of female data scientists, governments must first ensure that girls have the basic literacy and numeracy skills needed to connect to digital technology. A policy approach that focuses exclusively on developing skills in line with the higher levels of the pyramid is unlikely to expand digital participation. In fact, it may exacerbate existing inequalities, even undermining women and girls.