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Donor-database-analysis-and-Prediction-of-Donation-score

As a capstone project from masters in data science program at Seattle University, we worked with Camp Korey, a non-profit organization that works for the empowerment of children with a wide range of life-altering medical conditions.

This project helped the organization with donor database analysis and predicting donor scores. Below are the main analysis conducted:

  1. Identifying donors with mission contact information
  2. Analysis on gift growth trends over last three years(2020-2022)
  3. Analysis on gift giving trends over last three years(2020-2022)
  4. Segmentation of Donors into levels; Big and small donors
  5. Donor retention analysis.
  6. Calculation of engagement score from donation and volunteering score
  7. Prediction of donation score using Random Forest regression model and Neural Networks.

Skills used:

  • SQL and Python for data cleaning and EDA.

  • MS Power BI for visualization and creating reports.

  • Random Forest and Neural Network Algorithm using python libraries for predictive model building.

This project required extensive collaboration between non-profit liaison, professor and teammates. This demonstrates ability to work within a team and present the findings to leadership at the non-profit.

The project presented an opportunity for Camp Korey to make the most out of their data and improve fundraising efforts, ultimately allowing them to better serve the children and families they support.

Watch a short video here: https://www.youtube.com/watch?v=-Mj-1dY1hzk

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