About Me

Hi, I'm ChiChi! Welcome to my Portfolio

I am a recent graduate with a passion for exploration, problem-solving, and education. My data journey began during my undergraduate studies at the College of William and Mary, where I earned a Bachelor of Science in Biology. Additionally, I was able to complete a heavily quantitative-focused course load that earned my minor in Computational and Applied Mathematics and Statistics. It was here that I began developing my analytic skills and became proficient in Python and R, while also gaining experience with other software languages and programs.

My work experience after completing my degree is primarily in my role at a Veterinary Assistant in Emergency Veterinary clinics. During this time, I fostered my interest in data science by continually seeking articles and sources to delve into the realm of data analytics as a profession - with a particular interest in data analytics as it relates to veterinary medicine and healthcare. From here, I sought to enhance my data education and enrolled in an intensive bootcamp through the University of North Carolina at Chapel Hill. Here, I completed the course work with a 97% grade average and earned a certificate in Data Analytics.

Through my education, I have amassed and developed skills in data collection, organization, and analysis using various tools and technologies. I have a solid understanding of data analytics techniques - including, but not limited to, machine learning, dashboard building, data mining, and statistical analysis. I also have the strong belief that my diverse work experience provides me with a unique perspective that further enhances my problem-solving mindset and enables me to approach analytics with a strategic mindset. Working in veterinary healthcare has developed my skills in communication, quick and decisive thinking, and problem-solving.

I hope to utilize my skills and experience to perform effectively as a data analyst in any capacity and I am eager to further my education and knowledge in this field!

Technical Skills

Python

Primarily worked in Jupyter Notebook, Google Colab, and Spyder (Anaconda3).
Most used libraries: pandas, numpy, matplotlib, plotly

R

Primarily worked in RStudio
Most used libraries: dplyr, tidyr, ggplot2

SQL

Worked primarily with PostgreSQL, SQLite, and SQLAlchemy.

HTML

Used primarily in building simple webpages to effectively display data visualizations.

JavaScript

Experience using JavaScript in conjunction with HTML to create dynamic tables and maps.

VBA

Primarily worked with Microsoft Excel. Creating code to sort data, retrieve information, and also clean datasets.

AWS

Experience storing data in S3 and retrieving data to work with in PostgreSQL and Jupyter Notebook.

Git

Worked extensively with GitHub, GitLab, and in the GitBash terminal.

Tableau

Worked primarily with Tableau Public for dashboard creation and data visualizations.

Google Colab

Google Colab

Utilized during group work for more efficient communication and sharing of work between members. Worked primarily with Python.

Machine Learning

Worked primarily with python using the Scikit-learn and TensorFlow libraries.

Group Projects

Tickborne Illness Prevalence and Prediction

An exploratory analysis of tick prevalence in the United States and predictive measures of tickborne illness diagnosis in dogs.

Individual Projects

MechaCar Analysis

Analysis of the MechaCar dataset to perform statistical testing to garner insights about performance and production car prototype.

  • R
  • R Studio

Neural Network Charity Analysis

Developing a deep neural network model that can predict success potential of charities funded by AlphabetSoup company.

  • Python
  • Tensorflow
  • Machine Learning

Amazon Vine Analysis

Analysis of Amazon reviews written by members of the paid Amazon Vine program in order to potentially undercover biases.

  • PySpark
  • PostgreSQL
  • Google Colab
  • AWS

Bike Sharing

Exploring the CitiBike data set to create comprehensive visualizations in Tableau.

  • Python
  • Tableau

Cryptocurrency Data Exploration

Analyzing cryptocurrency data and using unsupervised machine learning models to uncover trends in the data that may influences investors.

  • Python
  • Machine Learning

UFOs

Presenting compiled UFO data in dynamic tables using JavaScript and HTML.

  • JavaScript
  • HTML

Mapping Earthquakes

Creating geographical maps that map earthquake data using JavaScript

  • JavaScript
  • HTML
  • GeoJSON data

Wall Street Stock Analysis

Using VBA in Excel to efficiently sort through and find specific information in a vast dataset.

  • Microsoft Excel
  • VBA