Starts Monday! Beginner Python & Math for Data Science Course. Enroll Now
BuildingCommunity in Data Science
Metis is committed to creating a culture of inclusion and diversity within the exciting and growing field of data science. We aim to foster an equal and representative data science community amongst our staff and within our classrooms, filled with individuals of all technical, educational, and personal backgrounds.
In the Classroom - Scholarships
Women, members of underrepresented demographic groups*, members of the LGBTQ community**, and/or veterans or members of the U.S. military are eligible to receive a $3,000 scholarship toward their Metis Data Science Bootcamp tuition. Why?
Women make up less than one-third of all employees in the tech sector and just 11% of data scientists1 – additionally, they are paid significantly less, on average.2
Women of color represent less than three percent of those in technology fields.3
Only four percent of those in software development, application, and systems jobs are African-American and just five percent are Hispanic or Latino.4
There are 20% fewer LGBT individuals in government STEM-related jobs than should be expected5 and 43% of the STEM workforce is closeted.g6
We must reverse these trends and create more avenues for talented individuals from these groups and communities to enter, remain, and thrive in the field of data science.
* Underrepresented demographic groups include African Americans, Mexican-Americans, Native Americans (American Indians, Alaska Natives, and Native Hawaiians), Hispanic and Latino Americans, Pacific Islanders, and mainland Puerto Ricans.
Building Strong Partnerships
To strengthen our pipeline of diverse students, and to support inclusivity within data science, we actively engage with organizations that serve underrepresented groups and communities.
We have teamed up with Women Who Code, PyLadies, Girl Develop It, Women in Machine Learning — and have created our own LGBTQ Data Science Meetup — to host and sponsor events and help with promotional support as needed.
We also find that conferences are a great way to get out of the office and classroom from time to time, to spend time discussing data science with others face-to-face. We have invested in sponsorships and/or have sought speaking opportunities at conferences such as Lesbians Who Tech, Grace Hopper Celebration of Women in Computing, and AlterConf, among others — all of which focus on underrepresented groups and communities within the data science and technology fields.
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