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In this special guest feature, Peggy Pranschke, VP Global Business Analytics with Vista, discusses how the barriers to success for women working as data scientist can be overcome. Peggy began her career in the federal government as a data analyst in 2005 where she worked in a variety of roles on various projects. In 2017, she left the government to lead AI and Data Science in the private-sector for Advance Auto Parts, a US-based Fortune 500 after-market auto parts retailer. At Advance, Peggy built a world-class data science team and created and implemented an AI strategy unique to the automotive industry. Peggy is also a passionate mentor and a member with Chief, a female executive networking group supported by Serena Williams and Madeleine Albright.

As organizations go through digital transformation, they generate more invaluable data that needs analyzing and interpreting. If done right, understanding these insights helps companies in every industry create customer value and gain a real competitive advantage.

As the amount of data increases and the demand for specialists grows, ensuring diversity within data teams should be a priority. Diversified staff can bring different perspectives, creativity, and unbiased problem-solving to the discipline. Yet, research shows that women are still significantly outnumbered in data-related fields. In fact, according to Boston Consulting Group, only 15% of data scientists today are women.There is clearly still a lot that needs to be done to increase the number of women in data careers and it is a shift that wont happen overnight. But there are several ways companies can ensure theyre helping drive this change.

Diversity-first environment

Building an effective team of data engineers and analysts requires true commitment to inclusion. Groups of employees with very similar backgrounds wont represent the spectrum of users that the products or services seek to target.

In practice, lack of diversity within a data team can lead to issues including representation bias and using skewed benchmarks when developing algorithms. Ensuring greater balance in the ratio of male and female data specialists increases chances that a potential bias problem will be quickly identified and flagged.

Another important step in making the workplace more gender-diverse is ensuring existing policies are helping to cultivate an environment of trust and safety. Some examples of inclusive policies include the possibility of async or flexible work, paid maternity/paternity leave, and anti-harassment policies.

Nurturing Talent

With the ongoing data skills shortage, attracting more women to AI and analytics roles has never been more pressing. One way of addressing this challenge is investing in the development of young women enrolled in STEM degrees. In fact, encouraging future female graduates while theyre still at university might be a decisive moment for recruiters its been reported that only a small portion of the group will opt for a career in data. To improve chances of more women choosing data and analytics careers, businesses could look into launching partnerships with universities and non-profits, offering women access to placements, insights and communities. At Vista, we have partnered with The Mom Project a talent community that connects professionally accomplished women with world-class companies.

Once you have an individual whos determined to work within the space, we need to ensure that the job descriptions they are seeing are appealing to a wider variety of groups. That is why closing the gender gap requires internal processes including recruitment tools to be as neutral and inclusive as possible. Otherwise, it can not only put female applicants at risk of unfair treatment but also make companies miss out on the right candidate. One way that employers can develop fairer recruitment processes is by using tools such as Textio to check job descriptions for inclusive language.

Companies often want to only take into consideration professionals who are fully equipped for data and analytics roles. To broaden the talent pool and increase the number of female candidates for these positions, we all should be looking for transferrable skills such as critical thinking and problem-solving.

Networking opportunities

Networking events are a great opportunity for women working in different tech fields to connect and share experiences. From my personal perspective, being part of Vistas Women in Technology (WIT) resource group and Chief, a womens executive networking group, has helped me immensely as a professional. Being part of WIT here at Vista has given me an amazing group of colleagues with shared experiences to learn and grow from. Ive learned so much from listening to how fellow parents tackle current challenges like working remotely while kids are in virtual school and balancing the two.

Although these events can be a valuable way of developing great ideas and enabling a better flow of information, I would argue that the format needs to be considered. Late night drinks and dinners are increasingly difficult to commit to. Changing up the format, for example, a breakfast or lunch event, could help to encourage more involvement.

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It's a Numbers Game Why Businesses Need More Women in Data and Analytics - insideBIGDATA