Name: Vanessa Tang

Year: Senior

Major: Neuroscience

Minor: Science in Human Culture

CFS Class: Field Studies in Public Health

Employer: Nousot

For CFS, I am a machine learning engineering intern at Nousot, a company that automates modeling and builds predictive and descriptive models. Much of my work deals with building and analyzing predictive models to better understand the strengths and weaknesses of each model. From building models and analyzing different datasets, I also work to improve models through data enrichment and hyperparameter tuning. During this process, I’ve researched topics in linear algebra and statistics in addition to machine learning and data science. Being able to diversify my skillset and branch out from traditional natural sciences was really important to me when applying to internships, and I am glad that I have been able to do so at Nousot. As a pre-med, neuroscience major, I’ve had to learn a lot on the job — from different machine learning models to data science techniques, all in Python, a programming language I had little experience in prior to this internship. Improving my programming ability has been one of the biggest challenges but also one of the most important skills I’ve learned in this internship. CFS has given me the opportunity to work as a machine learning intern and improve my coding skills despite my traditionally pre-med background. As today’s world becomes increasingly digitized, I knew that I wanted to learn how to code in a more practical setting rather than a classroom. Finding an internship through CFS has enabled me to do so, even with little background in computer science. Overall, my internship at Nousot has given me a good look into the world of machine learning and data science, two of the hottest fields in today’s digital world. Because of the good experiences I’ve had through CFS and at Nousot, this internship has motivated me to pursue a master’s in data science. In the future, I hope to combine my pre-med background with my experience in machine learning and data science to improve predictive health and personalized medicine.