Andrew Memme's Projects
Exploration, analysis and forecasting of crime density in Arlington VA from 2016-2024
ETL pipeline creation, utilizing selenium web browser for scraping snapchat desktop UI, pushing data into a g-sheet database and loading into reporting
Comparing sampling techniques and classification algorithms to predict credit risk
BG/NBD and Gamma Gamma probabilistic models to evaluate and predict customer churn, retention, and lifetime value of an e-commerce business
Analyzing sample election results
Analyzing theatre campaign data and providing insights on financial performance using Microsoft Excel
Exploratory analysis of a non-profit crowdfunding organization using Python and Tableau
Building an interactive earthquake map with Leaflet
Performing multiple regression to predict fuel efficiency (MPG) on an energy-efficient car model
Creating a data pipeline with movie-rating data - loading into a postgreSQL database.
Exploratory analysis of NYC bike sharing data with Tableau
Leveraging postgreSQL to organize data and determine which employees from a large company's database are up for, or close to, retirement based on their age and tenure.
Comparing the use of original data vs PCA in multiple regression. Analysis also showcases how principal components can be transformed back to their original vector space after model fitting for descriptive purposes
Random forest regression + ARIMA timeseries modeling to impute metric values and forecast revenue for reporting purposes.
Using Python3, Pandas, and Jupyter Notebook
Auto-ARIMA timeseries forecasting in combination with PELT changepoint detection to predict social media viewership performance and identify major changes in performance trends. Models are deployed into a streamlit webapp for analytical functionality.
Utilizing Python and R to perform statistical analyses on real-world snapchat performance data to discover how various metrics relate to viewership
Analyzing annual stock trends of Daqo New Energy Corp (NYSE :DQ) in 2017/2018 using VBA
Tokenization/Lemmatization vs keyBERT algorithms to analyze keywords and infer top performing topics on a subreddit of choice. Data is accessed via Python Reddit API Wrapper (PRAW).