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I’m a Data Scientist based in New York with a passion for understanding people through data. Leveraging my background in public relations and crisis management, I help data-driven companies tell their stories intuitively and meaningfully. I love chatting about machine learning, data privacy ethics and the attention economy. In my spare time, you can catch me searching for the best restaurant in the city.

This project automates Twitter hate speech detection with classification modeling. To prepare the data, 24,802 tweets were preprocessed using NLTK and RegEx. The final model was a Logistic Regression classifier that used CountVectorizer for feature engineering. It achieved a Recall (TPR) of 0.624 and an interactive version has been deployed on Heroku.

Time series modeling project to forecast LA reported crime rates based on 10 years worth of data. The final SARIMA model predicted the monthly average crime count, with an RMSE of 24.66. Exploratory phase discovered that the top 3 high-risk geographic areas in LA are 77th Street, Southwest and North Hollywood, with Latinx and Black victims being disproportionately impacted.

Binary classification project to predict whether oro not a client will default on their credit card. Baseline models included K Nearest Neighbors, Logistic Regression and Decision Tree models. By using GridSearchCV, the tuned Random Forest model was optimized and reached an F1 score of 0.5412.

This regression analysis project predicts house prices in King County Seattle, Washington. The dataset was sourced from Kaggle and included 17,290 rows of real estate data. Each iteration used feature selection methods to optimize each model’s RMSE. The final Linear Regression model achieved an RMSE of 214,529.87.

• Social Media Sentiment Analysis with VADER
• Jupyter Notebook Not Rendering on GitHub? Here’s a Simple Solution
• Tracking Keyword Trends on Google Search with Pytrends
• Titanic Survival Analysis — An Introduction to Tableau
• What is Cloud Computing? The Key to Putting Models into Production
• Chinese Natural Language (Pre)processing: An Introduction
• Adapting Data Science for Non-Binary Inclusivity
• Python vs R: The Basics

• Ethical Data Collection & Protecting User Privacy