Education is key
The World Bank Group released The Equality Equation: Advancing the participation of women and girls in STEM which shows that while girls tend to score higher than boys at science and maths in school, women are far less likely to join a STEM field. On a global scale there are still stereotypes about gender roles and what is perceived to be a masculine profession versus a feminine profession and removing this bias starts with education and training programmes. By removing the notions of masculine and feminine from a career choice, the field then opens to a much larger talent pool based on abilities and enthusiasm.
Hannah Lee, data scientist at Zurich and 2022 DataIQ Award winner for New talent or data apprentice, explained that “student outreach programmes can be extremely valuable to demonstrate the varied routes into a career in data. These routes are not always established through an academic STEM background. However, businesses can still pioneer initiatives to educate young females in STEM to encourage interest from an early age, which will ultimately improve confidence.”
According to The Equality Equation, “at the tertiary level, more women are enrolled in universities and have higher graduation rates than men around the world. Yet, women are significantly less likely to enrol in many (but not all) of the STEM fields. Women are well-represented in the life sciences but not in computer science, engineering, and physics.”
Lee added, “There are misconceptions that data careers are intimidating and require advanced technical skills, but that isn’t always true. All technical data skills can be learned and some of the most important skills, particularly in data science, include curiosity and creative problem-solving.”
Stereotypes within data and other technical professions still exist, but these are slowly being eroded and the number of women in senior positions is increasing. This is thanks in part to enriched workplace cultures, improved educational opportunities and a change in the way businesses approach candidates.
Business responsibility
Data businesses must shoulder some of the responsibility for developing an education culture that encompasses STEM careers. This can be achieved through outreach programmes to local schools for younger people, underrepresented groups and by establishing in-house apprenticeships.
“We are beginning to see that increasing the number of women in STEM is an important priority for many businesses in this sector through high-impact workplace training programmes,” said James Kelly, co-founder and CEO, Corndel and DataIQ 100 Most influential people in data. “To truly advance towards a data-driven future, skills must be developed and shared across the organisation, through upskilling. Once an organisation recognises the power of upskilling more women in STEM, they will quickly reap the rewards.”
Apprenticeships are a core way that businesses can encourage women into a STEM role with a data and technical focus. Lee has completed an apprenticeship herself and is keen to promote the programmes to other women. “I am a huge advocate for apprenticeships,” said Lee. “They allow businesses to source talent from grassroots and upskill individuals in a way that is relevant to business needs. Apprenticeships open up a more diverse talent pool with university being inaccessible to some, as well as improving the diversity of thoughts and experiences throughout data teams to drive innovation.”
There are multiple ways in which businesses can begin outreach programmes to local schools near their offices. The first is through collaboration, which is what the Anumana Code Academy has been achieving in Manchester.
“By having a presence in schools to educate young people on the opportunities of working in data and building excitement around data professions could initiate their career planning and expose them to different roles,” said Lee. “Those representing organisations should have an aspect of relatability to the audience if they are to leave a resonating impression and inspire the next generation. Evidencing successful career journeys from diverse backgrounds could have an exponential effect on the future diversity of the profession.”
Ultimately, work needs to be done to encourage women to enter data professions. Lee believes that “more excitement should be built around careers in data” and that “there need to be more female role models who can demonstrate their success in the data industry, the variation in establishing a career in data and the opportunities that are available.” If these views are followed, the momentum that has been lost building equality in data can be regained and the gender divide closed to the betterment of all data businesses.
