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  • Pittsburgh, PA

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Achievement: Pull Shark

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Achievement: Pull Shark

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cbrightly1/README.md

Hi, I'm Clare! 👋

  • ⭐ Analyst for the Allegheny Department of Human Services
  • 🎓 Master's degree in data science from Carnegie Mellon University
  • 🎓 Bachelor's degree in statistics and computer science from the University of Pittsburgh
  • 💳 2 years of data science and analytics experience in the financial services
  • 📊 4 years of independent consulting and research experiences

I am passionate about analytics and data science, with a strong belief that it's an art form of data engineering, statistical modeling, and business communication. My expertise centers on my ability to cultivate and engage in this entire process. The drive comes from my natural leadership skills, grit mentality, and strong curiosity. Then my technical skills, including SQL, Python, R, Tableau, Excel, and Power BI, allow me to contribute throughout the project.

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  1. capital-bikeshare-data-mining capital-bikeshare-data-mining Public

    Data mining process for a group project about the Capital Bikeshare data. Developed in Python using Jupyter Notebook.

    Jupyter Notebook

  2. stackoverflow-time-series stackoverflow-time-series Public

    A time series analysis of the StackOverflow question counts for popular data science topics. Includes SARIMA and VARMA modeling for mulitvariate time series in R.

  3. Text-Analysis Text-Analysis Public

    Collection of research projects developed in R for a text analysis course. Projects focus on core text analysis methods such as keyness, dispersion, MDA, etc.

  4. fnb-customer-segmentation fnb-customer-segmentation Public

    This project used a Kmeans after PCA model to segment retail customers to optimize marketing efforts. When the model repeatedly returned a single cluster, the model was used to prove the customers'…

    Jupyter Notebook

  5. fnb-leadgen fnb-leadgen Public

    This project uses a logistic regression model to develop a cross-sell list with current mortgage customers. Developed in Jupyter Notebook using Python for FNB.

    Jupyter Notebook

  6. housing-prices-project housing-prices-project Public

    Predicting market housing prices by testing algorithms taught in an intermediate data science course. Developed in R.

    R