All Times EDT
Keywords: Data Science, Economic Mobility, Skill Training
Real wages have stagnated for Americans without a college education, especially for those who have recently entered the workforce. The real median annual earnings of workers with only a high school degree aged 25-32 have, in fact, decreased from $31,384 in 1965 to $28,000 in 2013. Providing greater college access to workers employed in low-skilled and routine jobs is a potential solution for spurring economic mobility, but it is costly and typically takes several years. Viable alternatives are more sector-focused training programs that specifically target underprivileged. However, most job training programs for those with lower skills focus on preparing them for low-pay jobs and are heavily sector-focused. We started Cloud-Based Data Science Plus (CBDS+) Program that is a training program designed to serve underprivileged young individuals in East Baltimore. Rather than being strictly sector-focused, the program is “skill-focused” with the aim of equipping non-college attending individuals with competency in data science - a skill-set that has numerous applications and is growing in demand across a wide range of occupational sectors. It is estimated that by 2024 there will be a minimum shortage of 250,000 data scientists in the United States, and a report by IBM predicts the demand for data scientists will increase by 28% by 2020. The pilot phase of the program has already trained 8 individuals with GED background for jobs in data science and 5 of those have started as entry-level data scientists. We aim to answer the question of whether a program like CBDS+ that are not costly can improve intergenerational mobility for those who do not have the means to go to college.