
Closing the gender gap in data science and tech requires tackling barriers at every stage, from early education through career advancement, while actively challenging the unconscious biases that continue to hold women back.
Head of Statistics at Phastar

Closing the gender gap in data science and tech requires tackling barriers at every stage, from early education through career advancement, while actively challenging the unconscious biases that continue to hold women back.

Addressing systemic barriers and biases faced by women in research to foster a more diverse talent pool.