If you've come to check out things that I've done, I must apologize because there's not much to check out currently. Most of my Github work is locked in an Enterprise Github account since I focus a lot of my time completing projects for work. However, I plan to bring more fun to my personal page soon! 🎉🎉. Here is my LinkedIn profile; feel free to connect!

I am currently an Analytical Applications Engineer at Chubb. Previously, I worked at GE Healthcare for 7+ years in various analytical roles. I have a Bachelor's degree in Business Management, a Master's degree in Data Science, and an MBA with emphasis on Analytics. I use both R and Python but I prefer Python's robust data science toolsets (pandas, numpy, sklearn, etc). I have experience in the following areas:

• Data engineering tasks, such as:

  • Writing SQL code to pull data, create tables, & created stored procedures/views
  • Creating data prep & ETL pipelines in Python
  • Scheduling tasks to automate data flows

• NLP, mainly with nltk and spacy

• Building models in Scikit-Learn:

  • Linear/Logistic Regression
  • SVMs (both classification & regression)
  • Tree learners (including ensemble methods like bagging & boosting [xgboost])
  • Basic neural networks ❗area of interest❗

• Apache tools:

  • Hive 🐝
  • Pig 🐖
  • Spark with Scala backend ✨

• Cloud Platforms - I've done work on all major platforms (Google, AWS, and Azure)

• Creating modern data visualizations with:

  • Spotfire
  • Power BI
  • Tableau
  • Python (Ploty & Dash, Altair, Matplotlib, Seaborn, Bokeh)

I'm working to learn the more advanced machine learning frameworks for deep learning: Tensorflow and Pytorch. I'm studying and practicing the syntax for both and will be uploading what I learn here, along with other things I pick up along the way.