Women in data science careers worldwide

In our technology-laden world, data science touches virtually every industry worldwide. From manufacturing to education to product design to every major economy and its components, applying data to the world’s workings has skyrocketed in importance and will only increase in influence and necessity in the future. 

This infusion of data into the services, products, governments, and systems we all interact with affects everyone on the planet – men and women alike. This is why data-driven leadership has become even more important in 2021 and beyond. However, a significant disparity exists within the data science industry: the large majority of those working within data science are men.

When the voices applying data do not accurately reflect those that are cumulatively affected by it, bias skews the results and unequally serves the world’s population. A huge cocktail of factors has contributed to creating this reality. Slowly, the data science industry is becoming aware and taking steps to reverse it. Moving this effort forward and helping the data science industry itself more accurately reflect the earth’s population can have significant effects on the world at large.

The current outlook

A number of authorities and studies reflect the current state of the world’s data industry.

• A global study recently conducted by analytics firm Harnham revealed that only about 20 per cent of all data scientists around the world are women, which represents the lowest male/female ratio amongst the various STEM fields included in the study.
• Similar studies conducted worldwide report that about 30 per cent of the students that engage in higher-education STEM subjects are female, therefore still greatly outnumbered by the remaining male at about 70 per cent.
• A gender breakdown amongst major data science professionals across several distinct career types in the UK shows a significant disparity between males and females that can range from 10 to over 50 percentage points. Only one reported position (Management Analyst) showed an even split (50/50) between genders.

A multitude of forces perpetuate this reality. In many countries around the world, women are hampered from entering the data science field by cultural biases, restricted access to education, and fewer resources available to them to pay for schooling or for equipment/software.

Why is it important to change this reality?

The lack of female voices in the data science industry means that the process of collecting, measuring, and interpreting data to make decisions about the products, services, and systems that equally affect men and women is performed unequally by men. Wherever women aren’t involved, design, decisions, and conclusions will be biased towards the men that make them. The vast majority of the time, this does not happen intentionally or maliciously. It is simply an inevitable product of inaccurate representation. People don’t know what they don’t know.

Here is just one example of how this disparity affects real-life realities for people today: when crash test dummies were designed for the military, their proportions emulated the young male body (a logical choice considering women were not able to enlist at the time). However, that design choice migrated into most crash dummies used for consumer vehicle crash safety tests and persists today. Statistics show that women still experience a greater likelihood of serious injury in car crashes than men. If more of our crash testing was performed with an accurate reflection of both male and female bodies, this could be corrected.

What is being done?

Though this issue represents a massive international status quo that will take tremendous effort to shift, plenty of work is being done around the world to make that happen.

• Scholarships: A diverse spectrum of corporations, foundations, nonprofit entities, individuals, and other initiatives offer scholarships that enable women to take part in data science education or help to remove the barriers that prevent them from pursuing a career in data science.
• Events: A number of events meant to encourage women to pursue data science careers and support them in that endeavor occur around the world each year. These might be sponsored by higher education institutions in the United States or put on by a variety of other entities.
• Advocacy: Various organizations and initiatives create support, awareness, and community for women in data science or STEM fields.
• Visibility: Role models – seeing women thriving in data science careers – can be a key factor in encouraging the next generation of women to consider and pursue those careers. Major industry players are beginning to make inroads in helping elevate and champion their female data science employees. And many women in data science events include visibility and role modeling as one of their priorities in propelling systemic change in this area.

The vision

Achieving equal gender representation in the data science industry could change not only the landscape of the data science field – it would have ripple effects on design, decision making, and ultimately the possibility of equitable provision for entire industries. Helping make data science careers possible and compelling for more women around the world could, quite literally, aid everyone on the planet.