Gender Bias and Stereotyping

Challenge: Women in IoT data analytics often face ingrained gender biases and stereotypes that can hinder their progress and recognition in the field. This includes the misperception that men are more suited for STEM roles, affecting hiring, promotions, and project assignments. Solution: Overcoming this requires a concerted effort from both individuals and organizations. Women can seek mentorship, network extensively within their field, and assertively communicate their achievements. Organizations should implement unbiased recruitment and evaluation processes, promote diversity training, and establish mentoring programs.