● Built and tested Analytics application to predict a student’s financial growth trajectory based on their university, program, and related characteristics (approximately 1000 different columns).
● Compiled S&P Data from February 2020 to May 2020 and looked into how COVID-19 impacted the value of the Index
● Used Microsoft’s ML Studio to perform quantitative analysis to skim down the right set of characteristics.
● Utilized GCP Colaboratory, an advanced GPU/TPU-based computational Python runtime, to apply functional libraries like NumPy and Panda to build the predictive data models. Eventually, these models were deployed as RESTful consumable web services.