Over 10 years ago I left my childhood stomping grounds in rural southeast Missouri to pursue work and educational opportunities along the California coast. During this time, I received a B.S. in environmental resources engineering from Humboldt State University (See portfolio) and worked as an environmental consultant in San Francisco. Over the years of studying and consulting, I strongly gravitated to the data science aspects of my work, i.e. programming, statistical analysis, and modeling.
On February 10, 2017, I graduated from a three-month data science immersive course through General Assembly in San Francisco. Upon completion, I acquired competence in Python, machine learning, data visualization in Matplotlib and Seaborn, SQL, and Git by analyzing a variety of datasets, including an Ames housing dataset, a Yelp business characteristic and customer review dataset, and a categorized dataset of Facebook news posts.
My capstone project tackled the challenge of categorizing news as mainstream, fake, conspiracy, and satire. Model features included various user engagement activities and word usage in Facebook post messages. With the final multiclass logistic regression model, I achieved an accuracy score of 16% above the baseline on the test dataset.
I am eager to apply my core technical data science skills as well as my soft skills in communicating technical ideas to a broad audience in a range of projects from sustainability to finance. Please let me know if you would like to team up and work on a project of interest to you. I would be happy to help!