With a background in teaching math, I seek to get involved in the data science movement in education to provide more accessible and engaging learning platforms used in and outside of the classroom. I am very interested in the intersection between math education and data science and see so much potential for data transparency producing results on a large scale for students across income levels, races, and genders. As a teacher in a Title I school, I have seen how data can be used in both productive and destructive ways within the classroom. With this first-hand experience, I want to work towards the goal of accessibility of math education within low-income communities. I am also interested in the work behind increasing the number of girls and women in STEM fields, from both the learning and career perspective. Of course the two are not independent of one another, as increasing the number of women in STEM careers in part depends on increasing the number of girls extending their learning in STEM fields as students. I believe prioritizing equitable and bias-informed data science techniques within STEM learning platforms can contribute to a more accessible and inviting learning environment for STEM subjects and will work towards breaking down the current demographic and economic barriers to entry.