DATA GIRL SCHOLARSHIP
I am requesting donations to help spread awareness of underrepresented people who aspire to pursue data, business, and/or technology careers to the forefront. With your help, this scholarship's proceeds will assist a selected number of underrepresented people in covering the costs of a data certification or career resources of their choice.
The demand for science, technology, engineering, and math occupations is expected to grow during the next decade, but even with growth opportunities, women and some minority groups remain underrepresented, especially in the science and engineering fields (National Center for Science and Engineering Statistics, National Science Foundation Women, Minorities, and Persons with Disabilities in Science and Engineering, 2017).
MEET THE 2021 DATA GIRL SCHOLARS
I grew up in Guyana, South America, and two of the things I brought from my childhood were swimming and my curiosity for technology. Little did I know that these two hobbies of mine shared a sad truth: the lack of diversity.
I started college recently, and whenever I introduce myself as a prospective Computer Science major I would get the “surprised eye raises”. At this moment, I am the only black female in my computer science class and, not surprisingly, my college swim team. Data education, to me, means that I can contribute to Guyana’s human capital. Being a part of Guyana’s future means the world to me because I want to put my country on the map and I think technology can do that.
I grew up in an extremely diverse, yet segregated city that inspired my interest in healthcare disparities. After doing research on race corrections and racial bias in medicine, I landed an internship in a statistical genomics lab where I pursued my own research on what race could be defined as and the role it should play in medicine. Data education played a big role in this research as I had to analyze results from surveys and association tests. I look forward to pursuing research in college as well, so that I can further analyze biases in medicine through data and work towards making healthcare more equitable for all.