Articles & Resources

Sometime last year I read about a study looking at why there are so few women in data science. It resonated so strongly with my own experience that I looked it up again this week.

I included link to the full article below, but for me couple of points jumped out:

1. In the Unites States, 82% of female students view data science as highly competitive and exclusive (compared to only 64% of male students).

2. About half of students worldwide perceive data science as abstract and lacking in practical application.

Looking back, I can see how both of these beliefs profoundly affected my journey into data work. One reason it took me so long to settle into a data career is that I believed I would never be smart or credentialed enough to fit into the elite world of data science. Because of this (and some negative encounters with high school math teachers), I didn’t see a place for myself in the data realm for a very long time.

The focus on cutting-edge techniques and AI in data science was also a huge turnoff for me. I fell in love with analytics because it allowed my team to collaboratively solve problems and make better decisions. For me data is first and foremost about empowering people and making processes work better. My work is nothing if not practical and collaborative.

These days I proudly call myself a data expert, but it took me an unnecessarily long time to get here. That's why I'm determined to talk openly about my winding journey into the data world. We desperately need more diverse voices in data fields, and we are only going to get there if we make it very clear that there are many ways to be a data expert and that Data work can be human-centered, collaborative and inclusive.