Data Science Field Remains Unattractive to Many Female STEM Students

Data Science Still Has Gender Diversity Problems. New BCG GAMMA Study Sheds Light on Why Few Women Pursue Careers in Data Science-Related Fields, and What Employers Must Do About it

News provided by

Boston Consulting Group (BCG)

Feb 20, 2020, 00:01 ET

BOSTON, Feb. 20, 2020 /PRNewswire/ -- Data science has an image problem—and it's helping to fuel a critical lack of diversity. Almost 50% of female STEM students perceive data science to be overly theoretical and low impact. A sense that it is more competition-focused than other jobs is also behind their exit from the "talent funnel," according to a forthcoming report by Boston Consulting Group (BCG) and BCG GAMMA, titled What's Keeping Women out of Data Science? A significant share of STEM women across the globe also do not feel they have a good understanding of what a "data science career" is and what the day-to-day life of a data scientist in the workplace entails. The negative perception and lack of transparency combine to boost the gender gap: only 15 to 22% of data science professionals today are women.

Perception Mirrors Reality
Students around the world are picking up on an unfortunate reality: far too many companies still struggle to create real impact with AI, and many companies continue to lack a culture of collaboration in their analytics teams. The study reveals that nearly 75% of female data science majors are looking for exactly the opposite from their future jobs—namely applied, impact-driven work—while men are ambivalent. As long as companies approach and promote their data science and AI as theoretical endeavors without concrete and measurable value, female students will continue to be disproportionately deterred from entering the field.

Finding the Gaps in Understanding
BCG surveyed over 9,000 STEM men and women (each representing about half of the sample population) from Australia, Canada, China, France, Germany, India, Japan, Spain, the UK, and the US (with between 700 and 1,000 responses from each country).

Regarding transparency, the study revealed that only around 63% of men and 55% of women are well informed about the various career opportunities in data science. Even among data science and computer science majors, nearly half (47%) complained of poor clarity regarding career path options within the field. Australia, France, and Spain consistently achieved high rankings on transparency, while female students in China, Japan, and Germany consistently reported the lowest understanding of their options in this field. On perceptions regarding impact and purpose, China and Japan also appeared at the bottom of the list, while students in the UK, the US, and France had a more positive picture.

Companies Must Act
Despite these variations across countries, the problem is fundamentally a global one, impacting diversity across this rapidly growing field. "Companies cannot simply rely on the media buzz around AI, hoping for the job of data scientist to magically 'sell itself' to students," said Sylvain Duranton, Senior Partner and Global Leader of BCG GAMMA and an author of the report. "They must create a visible culture within their data science teams that celebrates impact and shuns competitiveness, and then make this career opportunity very tangible and attractive to students of both genders."

What Employers Can Do Better
While companies move toward a more purposeful approach to AI, they can also encourage diversity more immediately by becoming much more specific in their communication with students, directly addressing the concerns that women highlight as critical: the role of data science within the business, how data scientists work together on use cases, and how a career path in data science involves more than coding. They should be approaching students with real-life examples and value proofs, communicated by real data science practitioners who can make the day-to-day tangible and can directly address negative perceptions about work culture.

As long as companies do not get this right, a large (and disproportionately female) share of the talent pool for data science will continue to vote with its feet and avoid the field, perpetuating the recruiting gender gap in this increasingly mission-critical part of companies' workforces.

A summary of the findings from the forthcoming report can be viewed here.

To arrange an interview with one of the authors, please contact Eric Gregoire
at +1 617 850 3783 or [email protected].

About Boston Consulting Group
Boston Consulting Group partners with leaders in business and society to tackle their most important challenges and capture their greatest opportunities. BCG was the pioneer in business strategy when it was founded in 1963. Today, we help clients with total transformation—inspiring complex change, enabling organizations to grow, building competitive advantage, and driving bottom-line impact.

To succeed, organizations must blend digital and human capabilities. Our diverse, global teams bring deep industry and functional expertise and a range of perspectives to spark change. BCG delivers solutions through leading-edge management consulting along with technology and design, corporate and digital ventures—and business purpose. We work in a uniquely collaborative model across the firm and throughout all levels of the client organization, generating results that allow our clients to thrive.

About BCG GAMMA
BCG GAMMA is BCG'S global team dedicated to applying artificial intelligence and advanced analytics to business at leading companies and organizations. The team includes 800-plus data scientists and engineers who apply AI and advanced analytics expertise (e.g., machine learning, deep learning, optimization, simulation, text and image analytics) to build solutions that transform business performance. BCG GAMMA's approach builds value and competitive advantage at the intersection of data science, technology, people, business expertise, processes, and ways of working. For more information, please visit our webpage.

SOURCE Boston Consulting Group (BCG)