Amy Nguyen-Le Email and Phone Number

-Develop and maintain Data Standards, monitoring systems for compliance-Determine data architecture, ensuring information is actionable-Import and maintain data across multiple systems -Manage account, contact, campaign, and record creation-Manage duplication identification, merger, and inactivation processes-Participate in data privacy and security assessments-Lead data visualization and reporting efforts via PowerBI-Manage vendor relationships-Provide ongoing staff training of system processes-Perform additional ad hoc IT tasks

- Provide daily feedback and debugging resolutions of all curriculum assignments through one on one meetings and online code review. - Deliver supplemental lectures on various topics including, but not limited to data visualizations, feature engineering, Neural Networks and statistics driven analysis.

Conway’s Game of Life(A Cellular Automation Method created with Biology in mind by Jon Conway.) -Built an automated game from scratch using OOP in Visual Code Studios. -Used Pygame to generate visuals for the cells and game screen. Citrics(City data comparison website where users are able to compare the metrics between their city of choice to better their decision on moving.) -Sourced data from the US Census website and stored over 30,000 city data in MongoDB cloud services. -Collaborated with another data scientist on the time series model to show data trends for the next two years using FBProphet. -Built a recommendation model to show cities that best matches the user’s search preferences using KNN.Google Play Store Apps Project (Predicting the next popular application using the current high rating applications on the Google Play Store.) -Loaded and cleaned the dataset using Pandas and NumPy libraries. -Built the prediction pipeline using RandomForestClassifier and used XGboost to tune the parameters. -Showed visualizations with Matplotlib and Seaborn.Missing Migrants Project(Blog post with a Kaggle Dataset to show the numbers of missing migrants.) -Loaded and cleaned the Kaggle dataset using Pandas and NumPy libraries. -To show graphs and visualizations Matplotlib and Seaborn were used.