To be a successful data scientist, certain skills are essential – all of which are gender neutral. Despite
this, there is a gender diversity problem in this field. This vast structural constraint significantly affects
the quality of algorithms and subsequent business outcomes which impedes efforts to scale enterprise
data science programs to the next level. It is therefore imperative to understand the root causes and
develop proactive solutions which mitigate bias both within data science community and in algorithmic
As experienced consultants in the Advanced Analytics practice at Kearney, we have experience working
with both long-established commercial giants such as large CPG firms as well as new age digital natives,
across geographies. We have helped clients bridge the gap between present and desired states through
application of cutting-edge data science, analytics, and digital transformation. A striking reality that
comes across in all cases is the gender skew in the data science department and industry, and how this
hinders maximizing the company’s business output. We strongly believe that solving the gender issue in
the data science industry is imperative for business transformation in the new era.
There are three major factors contributing to this gender skew – long entrenched societal gender biases,
cloudy image of Data Science and archaic recruitment methodologies. We will focus on these issue
areas, what they mean in the business world and steps to tackle these head-on.
The data science industry will be worth USD 140.9B by 2024, and women need to be a part of this