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Nina Magnuson is a data scientist at GreatSchools.org. Previously, they were an analyst intern at Customer Marketing Group, Inc. from June 2017 to August 2017. There, they received advanced training in data pulling from Nielsen and IRI, data cleaning and analysis using Excel and presentation for client interface using Powerpoint. For their final project, they used bootstrap regression techniques to improve distribution analysis.

Before that, Nina was a risk analyst intern at McKeany-Flavell Company, Inc. from January 2017 to April 2017. There, they produced a model to predict stock value of 20 publicly traded companies in the food industry using data going back 20 years. Utilizing Microsoft Excel, R/R studio, and data mining and cleaning techniques, they applied school curriculum to real-world data. Nina created a model that can instantaneously produce predictions for all stocks given a multitude of changes from commodity prices to the weather in agricultural areas.

Nina Magnuson has a Masters of Arts in Statistics from the University of California, Berkeley. Nina also has a Bachelors of Science in Statistics/Economics from the University of California, Davis. Nina has also completed certification courses in Intermediate R and Intro to SQL for Data Science.