8 Women in Data & Insight to Inspire You in 2022
In the modern-day world, data is everything. It is fundamental for economic development. It’s developing our workforces, public policy, healthcare, and education to name the few. We rely on numbers to shape the ways in which we communicate and live. In 2020, every person generated 1.7 megabytes in just a second, and the big data analytics market is set to reach $103 billion by 2023!
With the importance of big data grows the importance of those responsible for shaping raw data — data scientists, analysts and professionals working in tech and STEM (Science, Technology, Engineering, and Mathematics) jobs. They are the ones advising organizational leadership on crucial business decisions which influence nearly every industry and market.
So, how is it that despite the importance of big data and these roles growing, the latest research shows that only 28% of Data & Insight professionals in the UK are women. In fact, while efforts have been implemented to improve the gender balance in Data, the percentage of female professionals has dropped from 30% to 28% in the past year…
The largest drop in the number of women was observed in Risk Analytics (17%), followed by the drop in Marketing & Insight (7%) which has always led the way when it comes to gender balance in the UK Data & Analytics industry.
It’s been reported that the gender pay gap has also increased since last year going from 10.5% to 13.5%. The reason behind the jump is unclear, but the evidence suggests this isn’t an education-based issue, with the pay gap remaining the same when both men and women have a STEM degree.
The Data & Insight industry is dominated by white men. We see it across organisations, at industry events and conferences, and on public forums. Women, ethnic minorities, people with disabilities, and those from disadvantaged socioeconomic backgrounds continue being underrepresented. The reason is a diversity problem in the STEM sector.
During school years (primary, secondary, high school) boys and girls tend to take math and science courses in fairly similar numbers. About as many girls as boys enter college prepared to pursue education in Science, Tech or Engineering. However, having completed the first year of college, significantly fewer women say they wish to pursue the major. Consequently, only 20% of those degrees are held by them.
In terms of workforce, women hold about 35% of STEM jobs in the UK. For Data Science, specifically, this percentage is much lower, with only 15% of data scientists being women.
Studies have identified several factors resulting in underrepresentation of women in the STEM sector, including stereotypes, self-assessment, student experience, and work biases. Increasing diversity in STEM and Data Science is a highly complex task, requiring work in many different areas. One is certain — we must start creating more inclusive academia and workplace cultures across the sector.
Data Science is shaping the future of industries and the world we live in. We cannot afford gender or other diversity gaps within the teams and industries promising to reshape our reality.
The lack of diversity within data & insight teams reinforces statistical bias. Building diverse data teams is not optional, it’s crucial for extracting accurate patterns and results from data sets.
Diversity within the field is essential if we want to minimise/eliminate algorithmic discrimination and machine bias. Non-diverse teams equal bias data, and bias data translates into flawed systems.
A good example of that would be Amazon’s, now scrapped, recruiting AI. The company’s hiring tool, designed to mechanise the search for top talent, used AI to give job candidates scores ranging from one to five stars. A year into using the experimental engine, the company realised it was not selecting candidates in a gender-neutral way.
