By Oliver Dewhirst, Senior Data Research Scientist at Exploristics
Gender imbalance in the world of technology is no secret. The figures show that women are underrepresented in STEM roles in the workplace. In the Data sector, male Data Scientists outnumber their female colleagues roughly 4 to 1. As a man working in the technology industry for three decades, it’s not often that I have found myself in a gender diverse team. In fact, it had never happened until I joined Exploristics.
This led me to question why men outnumber women in STEM roles? During my research I read the report from the Department for Education Behavioral Insights Team which investigates why there is a gender difference in STEM A level uptake.
Female students’ uptake of STEM subjects at A level
A level subject choice is a crucial point for gender diversity in STEM in the UK as it is the first time that students can choose between science or other subjects. Even though girls outperform boys in many STEM subjects at GCSE, fewer girls take these subjects at A level. This makes the pursuit of STEM higher education and careers much harder.
The Department for Education report applies the “expectancy-value” theory to try to understand this phenomenon. According to this theory, students make choices based on the expectancy of success in a subject and the perceived value of the subject in terms of importance, usefulness and enjoyment. Backed by academic work, the report suggests that stereotypes around STEM and gender lead to girls being less confident in their ability to tackle STEM subjects. These stereotypes are likely created by both parents and teachers. Compared to boys, girls perceive the value of STEM subjects to other subjects to be lower and they do not see their gender well represented in STEM.
I was keen to understand what attracted the female members of the Data Science Team I work in to A level STEM, why they ended up in science roles against the odds and if they encountered any barriers. Here is what I found out.
The STEM experiences of my female data science colleagues
Discussions with my data science colleagues Kim (Chief Data Scientific Officer), Sheila (Data Science Team Lead) and Data Scientists Amy and Aisling focused on their experiences of primary and secondary STEM education. The overriding impression that I got was a passion for science and the invaluable support of parents. Positive experiences during primary and secondary education, including the opportunity to participate in science competitions and STEM summer schools helped to encourage and shape their STEM journeys. However, despite these positive foundations, in some cases, I was saddened to hear that for some, significant and unacceptable barriers emerged during the pursuit of academic careers.
The wider benefits of gender diversity
The field of data science is responsible for creating algorithms, applications and systems that are used in many aspects of our lives, including finance, healthcare and influencing clinical trial design. A lack of gender diversity can give rise to skewed perspectives and biased results – crash test dummies are just one example of where a design that ignores women puts lives at risk. Fostering a diverse team can help to address this issue by mitigating bias in these systems, which leads to more effective and fairer decisions.
My experience working in a gender diverse data science team
During my time at Exploristics, I have witnessed firsthand how working in a more diverse team enhances collaboration, communication and decision-making. It feels like we benefit from the diverse points of view that come from different life experiences. And these results aren’t just anecdotal; they have also been found in academic research.
How Exploristics are helping to improve gender diversity in data science and STEM
I have also seen how the female data scientists at Exploristics actively engage as role models for young women coming through the education system by volunteering as STEM ambassadors and supporting the WISE campaign. Their visibility will hopefully inspire the next generation of women to pursue STEM subjects and steer us towards more diverse data science teams.