Women in STEM, particularly in data science, face systemic barriers including gender bias in hiring, lack of mentors, work-life balance challenges, insufficient networking, and a pay gap. These obstacles, along with disparities in education, confidence gaps, hostile work environments, and inadequate diversity policies, contribute to their underrepresentation in leadership roles.
Why Aren't There More Women in Data Science Leadership?
Women in STEM, particularly in data science, face systemic barriers including gender bias in hiring, lack of mentors, work-life balance challenges, insufficient networking, and a pay gap. These obstacles, along with disparities in education, confidence gaps, hostile work environments, and inadequate diversity policies, contribute to their underrepresentation in leadership roles.
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