Hello! I’m Camille. I just wrapped up my undergraduate degree from McGill University, where I majored in Honours Political Science and double minored in Economics and Anthropology. I’m interested in social policy research and passionate about leveraging data to create, implement, and evaluate better policies for low-income communities. Data science and rigorous research methodology clearly play an important role in this work, and I’m so thankful to be a part of the 2019 PODS program.
Moving to Chile at a young age made me passionate about fostering diversity in our cities, breaking barriers to secure employment, and having effective social safety nets. Around the end of my degree (better late than never!), I realized that what I loved most was using research to improve the economic and social health of the people I share my city with. I was drawn to the complexity and applied nature of social policy evaluation, but was always left frustrated by the reality that even though my degree equipped me with a solid understanding of the needs of different communities, I lacked the technical skills needed to find and implement solutions. Enter: PODS. By demystifying the world of data analysis and showing us how to ask the right questions, PODS has given me the analytical tools and confidence to start tackling such complex social issues.
After an intensive month of training on core data science techniques, I’ve been applying my new skills at Precision Analytics, a health data science firm in the Mile End area. Aside from petting our resident fluffy friend, Penny, I’ve been working with administrative units at a large Montreal University to analyze diversity in the health care professions. It’s well established that racial minorities and low-income groups are underrepresented in Canada’s medical schools, which leads to health inequalities and education gaps for these groups. To address this, universities often run pipeline programs with secondary schools in the hopes of bridging the gap between these communities and a medical education.
My work involves cleaning and analyzing survey data on these outreach programs, producing a report on our findings, and creating a dashboard with interactive maps of the Montreal area to help the University create effective pipeline partnerships. Apart from mapping areas with a high proportion of the target populations, these maps also display information on public schools and areas where previous participants have been recruited into the program. Equipped with this map, the administration can determine which areas to target in their outreach programs in order to diversify their student body and work towards eliminating health inequalities.
PODS is filling in a crucial gap by bridging the world of data science and policy-making. As data becomes increasingly available and powerful, there is a clear need for our policy-makers to be data literate. Bringing people from different academic and professional backgrounds together is crucial if we want to do social data science well, and I’m so thankful to have been surrounded by such a talented and diverse group. I look forward to using these skills in my next steps, and will forever be grateful to PODS and my cohort for such a formative fellowship!
