Women in Tech

Over the past decades, data science as a field has emerged as one of the most dynamic and influential global economy sectors. With data being hailed as the new oil, the significance of disparate prospects in the analysis and interpretation of this resource cannot be underestimated. The role of women in data science has proven pivotal as they break barriers, challenge stereotypes, and lead innovative positions shaping the future.

Historical Context And Progress

Conventionally, women have had under-representation in the technical fields. This trend overlaps in the data science sector, where most women have had to overcompensate so as to make their presence felt. However, the landscape is changing and women’s contribution in data science is steadily gaining momentum. Based on a report by Women in Data - a nonprofit organisation that is focused on creating awareness and educating women in the field of data and analytics, today, the global data science workforce is made up of approximately 30% women. This is a remarkable rise from the past records.

Increased awareness of gender disparities, rise of initiatives focused on motivating women to take active roles in STEM careers, and the growing recognition of the extraordinary insights women bring to the field of data science are some of the reasons for the progress made by women in data science. Programs like WiDS Worldwide, She Code Africa, Girls Who Code, and Black Girls Code are among the many mentorship opportunities that have played a pivotal role in supporting women in data.

Impact And Contributions

Today, women in data science have made valuable contributions across various industries. Their contributions have not only been felt by business enterprises, but the society at large. A specific example is Katherine Johnson, an influential female data scientist who is most known for her data analytical role for the US Freedom 7 mission, and calculations for the Friendship 7 mission. Florence Nightingale, the founder of modern nursing, was also a data scientist. An analysis led by Florence helped resolve that the majority of soldiers died from diseases and infections that could be prevented (Code Labs Academy, 2024).

Personally, I am a junior data analyst at Low-Income Financial Transformation (L-IFT), with a background in statistics and a trajectory in data science (L-IFT, 2023). As a woman, working with data in capacities such as visualisation and data modelling have enabled me to make informed decisions both for work and personal use.

Challenges And Recommendations

Irrespective of the headway, there are still several challenges faced by women in data science. Poor representations in leadership positions, wage gap, and gender biases are barriers that need addressing. According to a 2020 BCG study, women who have ventured into data science earn averagely 21% less as compared to their male counterparts - an issue that has kept a number of women out of data. Also, women find it difficult to balance their work and personal life, particularly in high-pressure working environments (Duranton et.al, 2020).

Diversity and inclusion are some of the approaches that organisations must prioritise in order to address these challenges. This should go to both hiring talents and putting up supportive environments which bolster growth and creativity. Mentorship and sponsorship opportunities, flexible working schedules, and ensuring equitable pay are vital steps in this direction.

Additionally, the significance of education and exposure to data science at an early age cannot be overstated. Girls should be exposed to STEM subjects at an early age.

Conclusion

Women in data science have ensured a continued growth alongside creativity in data. Their lone prospects and contributions are driving advancements which benefit the society in its entirety. Whereas outstanding progress has been made, there is still a huge load of work to be done so as to realize gender parity. Addressing present challenges and bolstering an inclusive environment enables us to make sure women in data science continue to break barriers and thus shape the future.

In a data-driven world, women’s voices are not just valuable, they are vital.

References

Code Labs Academy. (2024, June 5). 6 Impactful female data scientists. https://codelabsacademy.com/blog/6-impactful-female-data-scientists

Duranton, J., Erlebach, J., Brégé, C., Danziger, J., Gallego, A., & Pauly, M. (2020). What’s Keeping Women Out of Data Science?. Boston Consulting Group.https://www.bcg.com/publications/2020/what-keeps-women-out-data-science

L-IFT. (2023, July 20). L-IFT - L-IFT. L-IFT - Low Income Financial Transformation. https://l-ift.com/

Women in data. (n.d.). Women in Data. https://www.womenindata.org/