Aspiring data scientist with a passion for data visualization, data ingestion/manipulation and machine learning. Experienced in statistical modeling, data analytics, data wrangling and pipelining/ETLing, programming development, and facilitating IT and Business partnerships.
IT Specialist II, 10/2017 - Current
ENTERGY SERVICES, LLC, THE WOODLANDS, TX
Innovated several C# .NET Framework apps that execute VBA macros to gather and present real-time data; collaborated with business department.
Implemented deep learning hierarchical clustering model in R to find similarities between different power plants, embedded into R Shiny web application Engineered pathway for GIS data using spatial SQL joins to transport attributes from Oracle database into OSISoft PI AF data infrastructure tool via .NET (C#) programming.
Organized 250+ million rows of OSISoft PI time series data with R and condensed to ~5-6 million rows of digestible data.
Columnist/Analytics Research Contributor, 11/2016 - 06/2018
FANSIDED [NYLON CALCULUS]/DEF PEN, NBA, New Orleans, LA
Created interactive R Shiny web applications for O/U totals & 7-game series projections with multinomial logistic regression.
Communicated professionally in articles to interpret data and embedded Tableau diagrams that could be easily understood.
Performed text mining with Twitter analytics for word clouds and sentiment analysis.
Korean Basketball League Data Analytics Project
Built analytics database for Korean Basketball League (KBL) data in PostgreSQL (w/ psycopg2 library in Python).
Used Selenium w/ Python to extract raw text & tables, feature engineered Korean language data according to modern basketball analytics with Pandas & Numpy, and hosted database with Amazon Web Services EC2 instance.
Wrote R Shiny application with SQLite implementation of database for user interactivity and data visualization: https://steadylosing.shinyapps.io/KBLGameAnalyticsApp
Bachelor of Science, Systems Engineering Applied Science, 05/2016
Washington University in St Louis - St Louis, MO
Houston, TX 77022
R (& Shiny/Markdown)
.NET Framework, C#
OSISoft PI System
HTML/CSS Excel/Google Sheets
Languages: Korean – Intermediate
Medium, Explaining hierarchical clustering deep learning methodology for predicting NBA win%: https://medium.com/@SteadyLosing/revisiting-historic-teams-win-projections-with-interactive-sheet-cf03e2bddf86
Nylon Calculus, Predicting playoff berth success with Principal Components Analysis: Nylon Calculus: Predicting NBA Playoff berths and similar scenarios: https://fansided.com/2017/09/19/nylon-calculus-predict-nba-playoff-berths-similar-scenarios/
Def Pen, Twitter Wordcloud Sentiment Analysis: https://defpen.com/2017-18-nba-season-anticipation/