Data Science Talent / Gender Gap
Though slowly, but the gender gap in the professional world is tapering with women now making up 48% of the total workforce. The tech industry, with all its claims of being ground-breaking in all facets, is drastically lagging in this aspect. Furthermore, the field of data science has saddening statistics in the gender gap with the presence of only 26% of women (In the US). ‘Data scientist’ being the most demanded job world-wide and many reports state that only 11% of this post is occupied by females.
Several reasons have been accounted for the scenario with lack of mentorship for women in data science, lack of technical and mathematical education in early life, and human resource regulations not paying attention to the gender balance are the most prominent ones. Lack of positive role models along with the messages which young girls receive from gifts, marketing, and related media is also a roadblock in exploring such a wonderful world.
Influential women in Data Science Industry
There are several women with amazing credentials and spectacular results of their hard work . We have features
Corrina Cortes
A distinguished researcher of AT&T Bell Labs for a decade is now the head of Google Research. Her algorithm developing the Support Vector Machine, earned her the Paris Kanellakis Theory and Practice Award.
Daphne Coller
The co-founder of, “Coursera” is a leading expert of Probabilistic Graphical Models and the Chief Computing Officer at Calico Labs.
Alice Zheng
Senior Manager of Applied Science at Amazon heads the optimization team on ad platform and has the focus on building scalable models on machine learning.
Radhika Kulkarni
The VP of Advanced Analytics at SAS Institute is SAS CEO Award of Excellence winner and chosen as one of the 100 diverse corporate leaders in STEM.
Jennifer Vuaghan
Senior researcher at the Microsoft Research and an expert of data aggregation has numerous prestigious awards to her name.
Power of Women Data Scientists
The recent time has witnessed several initiatives prodding more women in science and technology at all levels but it is also important to realize the benefits associated with women handling such leadership roles.
Women tend to outshine at communications, problem-solving and fostering the team, which all are important qualifications for being a leader in data sciences. Women are more aware of the risks and sensing the vibes which is a big plus-point. Attributes like solution-oriented approach and data-driven decision make women a stronger contender for a position in data science.
These listed attributes have been affirmed by several surveys positively. OECD estimates that a half reduction in the gender gap can enhance the GDP gain by 6% in 10 years. McKinsey reported that gender-diverse companies have a brighter chance of outperforming the non-diverse ones by 15%. So it is clear that female presence creates a co-operative and beneficial environment.
Numerous ways have been advocated to include a better proportion of women in the field but it is more important to understand the social, cultural and financial benefits associated with the decision.
