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Professional Projects

As an experienced Data Scientist with a background in Marketing & Business Development, I've had the opportunity to work on a variety of projects that have allowed me to showcase my skills. I possess a wide range of programming language skills (Python, R & SQL), and excel in the use of machine learning and statistical techniques to extract valuable insights from complex data sets. I am able to translate business questions into actual SQL queries that return answers.  Furthermore, my ability to simplify complex information and effectively communicate it to diverse audiences is a key strength that I have honed throughout my career. Here are a few examples of my recent work:


The Power BI dashboard is a comprehensive, interactive visualization that highlights the multivariate correlations related to student retention in a college setting. The data was provided by University of the Pacific. Users can select various features to view their effects on student success rates. For example, by selecting a specific academic advisor, we can see how many students graduated from the college in total, per year, per ethnicity, per major, and per region.

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The Tableau dashboard is an informative visualization of child predator data. The data was retrieved from the Federal Bureau of Investigations website. The dashboard represents a statical analysis of 5 data sets. 

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Python & R
(Github Repository)

In addition to several data visualization projects, one of my core strengths lies in my ability to transform structured and unstructured data into clear and actionable insights. I am proficient in several languages (Python, R, HTML, SQL), data manipulation and analysis libraries (Pandas, NumPy, SciPy), machine learning frameworks (scikit-learn, TensorFlow, Keras, PyTorch), data visualization tools (Matplotlib & Seaborn), web scraping (Selenium & BeautifulSoup), and any other relevant data science technologies or methodologies. (Click on the chart image to see my Github repository.)

Excel + Google Slides

The pie charts were created using university student data and presented as part of a Google slide presentation on School of Engineering student churn/retention models. The pie charts depict the number STEM majors most commonly chosen and dropped by male and female students. 

Graph Database

The Neo4j Graph Database serves as a quick reference for IT personnel or Health Department workers to quickly see the employee hierarchical structure. This graph was created and queried using Jupyter Notebook with Python code. The code can be found on my Github repository ( 

Looker Studio with BigQuery

The multivariate, interactive dashboard created with Looker Studio serves as visual representation of California Hospital Ratings from 2016-2020. For this project, I first created a database using the multicloud, data wharehouse BigQuery and linked the database to the visualization tool Looker Studio. 

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