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The Growing Participation of Women in the Data Science Community


We still have a long way to go before the gender representation becomes more equalized, but the field at large indicates hopeful trends about women working in the role or desiring to do so in the future.



By Kayla Matthews, Productivity Bytes

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Research indicates data science is a promising career path, and it’s a field likely to offer job security and growth for the foreseeable future. Women are still significantly underrepresented, though.

Statistics across multiple studies confirm females only fill about 15 percent of data scientist roles, although some investigations show totals approximately 10 percent higher.

We still have a long way to go before the gender representation becomes more equalized, but the field at large indicates hopeful trends about women working in the role or desiring to do so in the future.

 

Rising Attendance at a Worldwide Women’s Data Science Event

 
In recent years, it’s been increasingly common for people around the globe to band together and stand up against school violence, a lack of support for the environment and science and women’s rights, to name but a few.

However, another event called Global Women in Data Science (WiDS) highlights the growing representation of female data scientists. Like the other events mentioned above, it’s too big for one city, but the anchor event happened in March 2018 at Stanford University and included a live-streamed conference that an estimated 100,000 people watched. Moreover, WiDS 2018 encompassed over 170 regional events in more than 50 countries.

Statistics from past events of this kind revealed a third of the participants are industry professionals, while the others are professors or students. The 2017 edition of WiDS attracted 75,000 people, and the details of the more recent conference mentioned above indicate attendance is increasing at an impressive rate.

 

More Providers Offering Data Science Options

 
Algeria is one of the largest countries in North Africa. The majority of its residents are under 30, and it has a higher-than-average unemployment rate compared to other nations in the region.

Code 213 is reportedly the first coding school in the country, and it aims to reduce the unemployment route through youth education. The educator offers four different tracks, including one in data science.

Each student will be immersed in a six-month program emphasizing a “learn by doing” approach. Then, they complete six-month internships. Code 213 also hopes to train at least 50 percent women through its programs.

At the university level, Saudi Arabia recently made history by training its first group of female data scientists through a partnership between Dell and Princess Nourah bint Abdulrahman University (PNU). PNU is the world’s largest university for women, and the program saw 57 students complete degree programs in data science or big data analytics this semester.

Dell previously performed an investigation and found a lack of workplace readiness was a substantial barrier for Middle Eastern countries wishing to be competitive in the digital age. The PNU program helps solve that issue. People in computer science must know numerous things to facilitate career growth, but solid academic teaching undoubtedly gives them a strong start.

 

A Promising Amount of Female Representation in Established Programs

 
It’s also an excellent sign that the universities that have offered data science degrees for a while report a more balanced gender representation than people might expect.

The University of California at Berkeley established a Data Science Division in the Spring 2016 semester and enrolled 300 students then. However, enrollment numbers for the Spring 2018 semester were over 1000, making the program the fastest-growing option in Berkeley’s history. A report indicates the gender balance is approximately 50/50, too.

Kennesaw State University (KSU) in Georgia also has a minor in applied statistics and data analysis. Representatives from the college say it stresses that people can study numerous things besides data science and still end up with that career path. At KSU, about 40 percent of the people in the data science programs are women.

 

Helping Girls Maintain Interest in STEM Careers Could Pay Off

 
When girls show an interest in science, technology, engineering and math (STEM) careers during their youth, the foundations could be laid for later data science work as adults. However, they often lose interest before it’s time to choose their college courses. A study by Microsoft and KRC Research aimed to find out why that happens.

It highlighted how if girls get encouragement from their parents, teachers and mentors, they’re more likely to stick to their paths than if they don’t have such feedback. Positive outcomes also increase when girls are exposed to inclusive classroom environments where people value their opinions.

An additional study investigated the perceptions of six-year-old girls and boys about gender biases related to an activity involving programming a robot. They found it reduced the gender gap in technology interest by 42 percent and increased self-confidence by 80 percent. However, researchers said the activity did not reduce ingrained stereotypes about which gender was better with robotics tasks.

They emphasized the need to teach STEM activities as early as elementary school. Moreover, they believe having women in STEM careers talk to kids about their work might help, but they hadn’t verified that theory before releasing the research.

 

Data Science Becoming More Diverse

 
These examples show that although the gender gap isn’t gone, it’s closing in the data science sector.

If people pay attention to the reasons why girls lose interest in STEM too and try to minimize them, even more progress should become evident.

 
Bio: Kayla Matthews discusses technology and big data on publications like The Week, The Data Center Journal and VentureBeat, and has been writing for more than five years. To read more posts from Kayla, subscribe to her blog Productivity Bytes.

Original. Reposted with permission.

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