DataRes at UCLA
Daniel Neufeldt is a Mathematics, Data Theory major at UCLA, expected to graduate in 2024. Daniel has gained diverse experience through multiple internships, including a role as a Data Science Intern at Southern California Edison in 2024 and a Data Analytics Intern at GOBankingRates earlier in the year. As a Machine Learning Research Assistant with the UCLA Psychology Department, Daniel contributed to Random Forest research for text classification. Additional experiences include working as a Data Analytics Intern at Pacific Life and a Bioinformatics Research Assistant at UCLA Health, focusing on automation of statistical tests and visualizations. Prior to these roles, Daniel worked as a Tutor at Kumon North America and briefly as a Construction Worker. Educational background includes a High School Diploma from Shorewood High School and a Korean School for Language and Culture diploma.
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DataRes at UCLA
DataRes @ UCLA is founded by data enthusiasts who love solving problems and crafting stories with data. We provide a platform for aspiring data scientists and analysts to work on savvy data projects outside of class that are geared towards making an impact. If you love playing with data, creating powerful visualizations, analyzing hidden trends or building predictive models, we would love to have you on the team. We have 2 main teams at DataRes: 1. Research: Members of this team work on complex machine learning and deep learning problems involving the implementation of high-level machine learning and statistical models. 2. Data Blog: Members of this team work on analyzing datasets on all possible topics and presenting it to a cross-functional audience by the means of an article.