Intro

Data Scientist with a strong background in Biology and Mathematics. Skilled in implementing Machine Learning to solve business problems. Experienced in Python, Jupyter Notebooks, SQL, Scikit Learn, Seaborn, Matplotlib, Data Visualizations and Experimental Design. Recent projects include implementing Machine Learning to derive actionable insights, Data Modeling and Report Design. Check out my work.

Work

Solved a business problem and predicted future Median Ppsf. Evaluated how well the models predicted Median Ppsf based on past trends and new COVID data.
Predicting Median Price Per Square Foot during COVID PowerPoint deck.
Predicting Median Price Per Square Foot during COVID Jupyter Notebook.

Divided existing and potential customers into sub-groups of consumers based on some type of shared characteristics. Used various unsupervised learning models such as K-Means, Hierarchical Clustering, Gaussian Mixture and DBSCAN.
Customer Segmentation from Sales Data

Solved a business problem and predicted customer Churn. Evaluated how well the supervised learning models predicted customer churn based on observed customer churn data.
Telco Customer Churn (achieved 93% accuracy)

About

I am a Visualization Data Analyst at Stab Magazine. I've learned industry best practices and modern data science/analyst standards alongside a senior data scientist mentor. I've developed and presented projects involving machine learning, exploratory data analysis (EDA), data cleaning, statistical modeling, study design, statistics and probability.

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i = 0;

while (!deck.isInOrder()) {
    print 'Iteration ' + i;
    deck.shuffle();
    i++;
}

print 'It took ' + i + ' iterations to sort the deck.';

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Item One Ante turpis integer aliquet porttitor. 29.99
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