Data scientist, educator, and teacher trainer focused on promoting data-informed decision making who is adept at explaining complex concepts to non-technical audiences. Lifelong learner who sees everyday as an opportunity to learn and share.
Stakeholder Management
Python: pandas, BeautifulSoup, scikit-learn, TensorFlow
R: dplyr, rvest, tmap, ggplot, forcats
Software: SPSS, JMP, Winsteps, FACETS
General: git, Bash, AWS
SQL
Topics: webscraping, machine learning (XGBoost, LSTM) and computer vision
Analysis of #PodRevDayTopics: Twitter scraping, descriptive statistics, and data visualization
Promoting the understanding and adoption of machine learning
Educators R LearnersUsing R for creating visualizations to expalin data
Teaching Learning Learning TeachingHighlighting edtech use cases and best practices