Know How Data Science Is Helping Women Break the Industry Stereotypes
Women have created their presence and have positively impacted the field of technology. We can't deny that some of them have reached the zenith of success, and others still strive to do so. With the upcoming trends in the technical field, women in data science have persistently pushed and proved themselves.
However, the road is long and needs to empower women in new and developing fields. According to BCG research, the percentage of female data scientists in STEM (Science, Technology, Engineering, and Mathematics) disciplines is only 15-22%, which still manages to increase with the upcoming trend.
Even though there is a lot of gap between the percentage of females and males in the field of Data Science (DS), there are still optimistic approaches encouraging women to get entailed with data science opportunities. Many companies have also suggested considering women co-workers to be more beneficial and promoting them to step into the field of data science.
In these regards, the Women in Data Science (WiDS) at Standford University has taken a good initiative. Since 2015, they have been inspiring women worldwide in the field of AI and (DS) through global data science conferences, Datathones, workshops, etc.
Now, let's explore what facts regulate women in data science and what career advancement can be as a data scientist.
The Gender Gap Breakdown
There has always been a gender disparity for women in offices and outside work. However, many steps have been taken to improve this situation in recent years, and voices have been raised.
As mentioned, the global voice of Standford's Women in Data Science (WiDS) conferences has greatly helped. Still, in third-world countries, there is no significant improvement in the gender pay gap for women.
This is evident in our post-pandemic world, where millions of women lost their jobs or received pay cuts. Add to that the additional responsibilities they felt in their homes.
In fact, such pressurized add-on responsibilities led to a performance lack in most women. And the final result was layoffs or pay cuts. This happens irrespective of the field-tech or nontech.
But still, in such a critical phase, so many women redefined their careers. And the medium has been (DS) and artificial intelligence.
According to a MetLife survey, 2 in every 5 women consider pursuing a career in STEM, but they struggle. If you properly research, then you will find that in the last 3 years, so many women professionals achieved successful career transitions through data science. Even a number of them are now well-established as senior data scientists in different MNCs.
Take the example of Mathangi Sri Ramachandran. She is among the famous female data scientists with nearly 18 years of experience creating leading data science products. She is currently a chief data officer at YUBI and has been named one of India's most inspiring women in data science. She has written two informative tech-related books on 'Practical Natural Language Processing with Python' and 'Capitalizing Data Science.'
Related reading: Women in AI - Top 10 Indian Women Empowering the World of AI
Why is Data Science a great career for women?
Data science offers lucrative job potential. Undoubtedly, the pay comes as a factor attracting the most candidates. Still, (DS) is an industry that is thought to be difficult. But this is not true.
There are two reasons why women should consider data science as a career:-
Reason 1: Best available opportunities for highly paid career transition
During the pandemic, we observed a significant downward trend in jobs.
Especially nontechies who were affected the most. But a lot of such women has already revived their career through AI and DS.
In times of crisis, learning a valuable skill set and switching to a data science career (semi-technical or technical) can provide job security for an extended period of time.
Because data science is not at all only for techies, there lie so many other positions that nontech women can also enter. The only thing they need is an industry-standard data science course. Women can also utilize their career break (due to reasons like maternity or any other family reason) to learn data science. This can help them in getting a stunning comeback.
Reason 2: Ample and faster growth opportunities
The second reason for selecting (DS) is that it has a lot of career opportunities with prolonged growth in the future. Additionally, pursuing a career as a data scientist provides the highest salary growth as compared to other professions. The increase in competition continuously boosts the salary growth of data science professionals and senior data scientists.
Reason 3: Women can get the most positive work culture
We can't deny that when it comes to family and professional life balancing women's needs has some added responsibilities. From this aspect nowadays renowned MNCs offer better work-life balance with a quite positive work culture. So women can better manage their families without compromising their careers.
What is the qualification to join a career as a Data Scientist?
The knowledge of high school-level math and basic coding knowledge is enough to start with data science. In fact, even if you don't know how to code but have a passion for coding, you can still opt for a data science career transition. A coding ninja or stat expert is not at all the mandatory criteria for entering the (DS) field. Also, you don't need an undergrad or post-grad degree in the same. But yes, once you enter this field, you have to upskill yourself to master all the ninja techniques of data science.
Is it difficult for women in data science to pursue a long-term career?
Women don't generally continue with a career in data science as they are discouraged for several reasons.
These are
Gender pay disparity
Male-dominated workplace environment
Poor career development
Gender discrimination in recruiting
Lack of accessibility to mentors
While many of these issues are absent in the data science career, there are still several misconceptions that remain the same. Therefore, women in the data science field show a declining trend, which can easily be solved by encouraging more women to pursue a technical career and educating them on the benefits.
To become a professional data scientist, you must go a long way. It doesn't seem easy, but it can be easily achievable.
The easiest and most capable way to achieve a data science career is to pursue online and offline data science courses. It will help them with ongoing trending projects and certification. A well-recognized certification can help you make a prospective and successful background in subjects related to (DS).
Further, completing the courses and projects, an internship can be a reliable solution. Working as a data scientist at an intern level can help you know how the industry works and the future implications of working as a data scientist.
Therefore, women in data science may find it difficult to comprehend topics, but so do men, whereas, with the proper guidance and following the right learning path, it can be easily possible.
How are women narrowing the gender gap?
Women in the data science field have basically narrowed down the technical gap, which was earlier in an extended stage. Today most women are trained and comprehend technical knowledge. They have found their way to stand out from the crowd and make a perfect place in any tech organization.
Especially during and post the lockdown period, so many female professionals have upskilled themselves, and now they are happy enjoying a lucrative career in data science.
What are the methods to enhance Data science for Lucrative career?
The key factor in this field is practice and persistence to find meaningful information. A data science and AI course followed by a perfect internship program is the utmost prominent need; it will provide you with the necessary tools and knowledge as a data scientist.
No matter your educational background, even if you don't have computer science knowledge, you can pursue a career in data science with the right course.
But yes, most candidates make the biggest mistakes in pursuing a generic course. To have a successful career transition, you need to choose a domain (as per your work experience) specialized course only.
Your best option is a Data Science and AI program that provides experienced mentors, domain electives, and flexible study. You can learn and practice through data science professionals and MAANG experts who can provide valuable knowledge on an industry-based capstone project.
What are you waiting for? Enrol in a program and start learning.
