Data Analytics Engineer
Skilled in Python, R, SQL, Windows/Linux, Git/GitHub, Tableau/Looker/Power BI, Excel/Google Sheets.
Tracking and planning your budget is a necessary first step in your journey to financial freedom. In this YouTube video, I share budget tracker templates in Google Sheets for individuals, couples, or families. Through this, I outline how to connect Google Sheets and Google Forms for streamlined data entry on the go, allowing your budget tracker to perform all of the calculations for you.
My team and I recently competed and placed as Global Finalist Honorable Mentions in NASA's Global Space Apps Hackathon, putting us in the top 102 out of over 5,500 competition entries. We developed a recurrent neural network (RNN) to predict the Kp index, a measure of geomagnetic activity, using data from the DSCOVR satellite. DSCOVR is an early warning system for solar wind conditions traveling to Earth, making it ideal for predicting the Kp index. We also outlined an approach to utilize data from the Canadian Space Agency for further validation and fine tuning of the model over time. This research has the potential to improve the accuracy and timeliness of space weather forecasting, which could help to protect critical infrastructure and human populations from the harmful effects of solar storms.
This is my second implementation for creating PDF reports of my Oura ring data for my doctors and I. This time I utilized python for extracting data from Oura's API, transforming it, and loading charts into a streamlit dashboard. It was fun to finally play around with streamlit, although it's much better for web apps/dashboards than PDF reports.
With this DataCamp competition, I used messaging data for an international company to create a graph network. Utilizing graph theory, I identified different types of centrality to assess the strength of the network as well as which departments are most central to the organization.
I took part in a DataCamp community competition to pull insights and build a forecasting model for a meal delivery service in India. Utilizing R, I was able to use a multiple linear regression model that produced an adjusted R-squared of about 0.7 with the training set. While the test set had a correlation coefficient of 0.83 with my model.
Using Python's BeautifulSoup package for webscraping, we compare the distribution of release years for movies and shows ranked in IMDB's Top 250 lists. This provides some insight into whether or not we are in the "golden age" of TV shows compared to movies.
To end 2022, I created a Tableau story to enter into a DataCamp certified community competition. Although I didn't win, I had a blast getting practice with tableau and learning more about some of the history of the FIFA World Cup through data.
Being able to use R to connect with a SQL database while running SQL queries is widely beneficial by opening up more possibilities with your work. Here I was able tro replicate some of my previous work performing some EDA with European Football data.