Having just received my Masters Degree in Data Science from Southern Methodist University, I am passionate about leveraging data to solve complex problems with creativity and drive insightful decision-making. During my master's program, I honed my skills in machine learning, statistical analysis, and data visualization and developed hands-on experience with Python, R, SQL and greatly expanded my data science toolbox. As a bilingual professional with a diverse academic background, including a Bachelor's Degree in International Relations and Global Studies from the University of Texas at Austin, I bring a global mindset and excellent communication skills to collaborative environments. My journey from international relations to data science underscores my adaptability and eagerness to integrate diverse fields of knowledge. I am driven by a relentless curiosity and a passion for continuous learning. I thrive in dynamic, team-oriented settings and am committed to contributing to the success of innovative data-driven projects.
Languages: Python, SQL, R, HTML5, CSS3, Git, JavaScript
Databases: AWS, MongoDB, MySQL, Postgres, pgAdmin
Applications: Github, Flask, Command Line, Tableau
Tools: Excel, TensorFlow, Pandas, Jupyter Notebook, Scikit learn, Matplotlib, Bootstrap
Using Python and the Hugging Face transformers library, developed a music genre classification using DistilBERT transformer model to capture and understand intricate linguistic nuances within song lyrics to enhance classification accuracy and efficiency.
Using Python’s TensorFlow library, the purpose of this project was to create a mathematical driven solution to design and train a deep learning neural network to analyze the impact of each donation to a charity, predict which organizations are worth donating to and which are high risk, and evaluate whether the foundation money was used effectively. Final model evaluated all kinds of input data and produced a clear decision-making result.
CodeAutomated script using Selenium webdriver that checks for vaccine appointment availability.
CodeUsing unsupervised machine learning, this script analyzes a database of cryptocurrencies and creates a report including the traded cryptocurrencies classified by group according to their features.
CodeThe purpose of this project was to analyze 2016 and 2020 election and COVID data and make predictions using machine learning models such as a Linear Regression Model and Clustering and create a visualization of the data in Tableau.
Code Tableau DashboardThe purpose of this script is to predict credit risk by employing different techniques to train and evaluate models with unbalanced classes
CodeThe purpose of this project is to analyze green energy stocks and create an Excel workbook including an easy-to-run VBA macro able to analyze an entire dataset of stocks. This tool will help him in its financial expertise.
CodeThe main purpose was to use Excel to analyze different Kickstarter fundraising campaigns to compare them in relation to their launch dates and funding goals in order to uncover trends and help the client to adjust its future campaign projects in the U.S. and Great Britain for the best results. In order to do this, we needed to organize, sort, analyze crowdfunding data wanted create visualizations based on our findings.
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