5 Ways To Empower More Women In Data Science
Although data scientist is the most favoured profession of 2020, according to reports, only 30% of the position is employed by women. It has been believed, by experts, that more gender diversity, particularly in the field of data science, can translate to more significant innovation, increased productivity, and better decision making. However, several companies still lack basic diversity in their organisation. Despite several benefits, many companies across the globe still struggle to balance their work in terms of diversity. And, this disparity gets even higher when it comes to senior-level management positions. It is proven that women bring a different perspective to business and therefore, it is extremely important for the data science experts to fill this gap by empowering more women in data science. In this article, we will discuss a few ways for an organisation to combat this gender gap. Encouraging Women With STEM Background With every organisation looking to build data science teams, more jobs are being created than recruiters can fill them due to lack of skilled workers in the field. To fill this gap of talent shortage, organisations can encourage more women with a STEM background. The absence of women in the data science field is significantly evident, and organisations are therefore missing out on deploying some valuable skillsets. It is believed that customers prefer companies that are diverse enough and employing more women in tech. One of the key ways to encourage women with a STEM background is by introducing STEM itself from an early age. The data science field needs to make female role models more apparent for the younger crowd, which will give them someone to look up too. Furthermore, it is also essential to create initiatives and discussions around female empowerment in schools and universities. Creating Women-Friendly Diverse Organisation Another way of encouraging more women in this competitive data science field is by creating a women-friendly diverse organisation, where women are not stereotyped to a particular role. Usually, organisations have cultural imbalance along with financial ones, which in turn changes the ratio of the workforce. To change this difference, it is imperative for leaders to improve opportunities for a female executive in their organisation. A similar pay along with leaves should be offered to women data scientists who are working in this field. Another critical factor for an organisation to be women-friendly is by introducing policies that are equal to both the genders. Women friendly organisations should display empathy towards female executives and should be given equal priority during project allocation, pay hikes etc. Conferences That Allow Networking Organising conferences and workshops that allow networking is another great way of encouraging more women to meet their peers and discuss the field. Being active in your field can bring many benefits. Not only does it allow you to meet other data scientists, but it also allows you to spread the word of your work and your colleagues’. Such networking could uncover ideas and could spark inspiration among peers. The Rising is one such meet for women data scientists that celebrates women innovators in data science, analytics and AI fields. This conference serves as a forum for exchanging ideas to build a better platform for women in technology. This event has been designed to bring in women from STEM backgrounds and share their career interests in data science. With over 250+ participants and more than 15+ talks from industry leaders, The Rising inspires more women participation in analytics careers. Such conferences and workshops could provide a platform for women visionaries to dive into the field, share their perspective, and encourage more young women executives to build a career in this buzzing field. Find Mentorship To Enhance Your Skills Another way to encourage more women in data science is to encourage more mentorship. Young executives should find the right mentor for themselves who can help them in their career path. Mentorship not only bridges the knowledge gap but also helps in improving their skills regularly. Having a right mentor would help students to build a relationship with their future leaders, and test his/her work-readiness before embarking on a full-time job. Alongside it allows students to upskill themselves according to industry requirements. Mentorship gets valuable for both sides — students gain valuable tips from older executives, and for companies, mentorships can act as a first filter for data-centric roles. Most amateur data scientists are unclear about their job role, and mentors can indeed fill this gap by sharing their insights and knowledge of the industry in-real. Encourage Women For Leadership Job Roles Lastly, organisations should not limit women executives to only subordinate roles but should encourage them to apply for leadership job roles. It has been seen that men usually apply for a job when they meet just 60% of the job requirements, while on the other hand, women only apply for jobs when they meet 100% of the requirements. With this fact in hand, organisations should encourage women executives to change this by applying for jobs that they desire. Changing the mindset of women is another big concern for not having many women data scientists. In this fast-paced skill-driven era, the demand is getting higher day-by-day and organisations require more enthusiasts coming up applying for jobs and upskill on the field. Just a few days away now, The Rising 2020, which is to be held on 20th March in Bengaluru has created a buzz around the tech community. The Rising is a great place to meet and support women developers and professionals in the data science field. Book tickets for The Rising 2020 here.
Although data scientist is the most favoured profession of 2020, according to reports, only 30% of the position is employed by women. It has been believed, by experts, that more gender diversity, particularly in the field of data science, can translate to more significant innovation, increased productivity, and better decision making. However, several companies still […]
In this article, we will discuss a few ways for an organisation to combat this gender gap by empowering more women in data science.
["Data Science", "data science women", "Women in Data Science"]
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["AI", "data science", "analytics", "RAG", "R", "GAN", "ViT", "innovation", "programming_languages:R", "data_tools:Spark"]
Sejuti currently works as Associate Editor at Analytics India Magazine (AIM). Reach out at sejuti.das@analyticsindiamag.com