Biography

I’m a Data Scientist at Comcast Corporation on the Reliability Analytics & Data Science team. I'm passionate about using data science and machine learning to generate insights that address both theoretical and real-world problems. As a data enthusiast and former graduate student researcher in Experimental Cognitive Psychology, I’ve gained extensive experience with quantitative analysis, advanced statistical modeling, and communication, leveraging my undergraduate minor in Computer Science to use a variety of programming languages and statistical software (e.g., R, Python, SQL, MATLAB, JavaScript, SPSS) to suit the problem at hand.

Before joining Comcast, I graduated from Washington University in St. Louis with a Master's Degree in Psychological & Brain Sciences and a Graduate Certificate in Quantitative Data Analysis, where I explored the mechanisms that underlie retrieval from long-term memory. As a graduate student I was a National Science Foundation Graduate Research Fellow and a United States Scholar in the McDonnell International Scholars Academy.

Prior to graduate school, I completed a B.A., summa cum laude, in Psychological & Brain Sciences (concentration in Cognitive Neuroscience) and a minor in Computer Science at Washington University in St. Louis.

M.A. in Psychological & Brain Sciences, January 2021

Graduate Certificate in Quantitative Data Analysis, Requirements complete 2019

Washington University in St. Louis

B.A. in Psychological & Brain Sciences, 2016

Minor in Computer Science

Washington University in St. Louis

Programming Languages: Expertise: R, Python (e.g., numpy, pandas, sklearn), MATLAB | Experienced: SQL, PHP, HTML, CSS, JavaScript

Data Visualization: Expertise: R (e.g., ggplot), Python (e.g., matplotlib, seaborn), Prism, MATLAB, Excel | Experience with: Chart.js (JavaScript)

Database Management: MySQL, phpMyAdmin | Data Collection: Amazon Mechanical Turk (MTurk), Qualtrics, neuroimaging

Machine Learning & Analytics: Regression & Classification Techniques, e.g., Linear Regression (Simultaneous analysis & hierarchical model comparison), Mixed-Effects Modeling (Multilevel Models), Logistic Regression, KNN, Random Forest, AdaBoost, XGBoost, Neural Net | ANOVA, ANCOVA, t-test, Correlation, Signal Detection Theory (d’, Type I and II error), ROCs, Effect Size, Confidence Intervals, p-value | Big Data: Experience: Cloud computing w/ AWS EC2 instance, AWS Athena | Exposure to: Spark, EMR

Misc: Expertise: Microsoft Excel, PowerPoint, Word, SPSS, Chrome DevTools, Hypothesis Testing, DOE | Experience: Agile work environment, Confluence | Music writing and production