Collaborating with Data Architecture team under Enterprise Data Services to support and optimize the company's data infrastructure

• Lead a team of eight in developing a dynamic in-game wagering model, utilizing data-driven projections and economy simulations• Designed and implemented a comprehensive XP and currency system for an upcoming game, ensuring a balanced and engaging player experience

• Spearheading a data-driven approach applying optimized traveling salesman problem based algorithm to model and analyze racial disparities from 90,000 rows of racial makeup by blocks data in Los Angeles.• Demonstrated expertise in quantifying accessibility to transport based on race entropy and visualizing geographic patterns across Census datasets using Python, R, and Operations Research tools

Working on a software solution to automate the required data governance process• Automated data cleaning and data transformations with a front-end application for the Global Operations team to support data-driven decision making processes by saving an average of 20 minutes (90%) of manual processing per file• Managed data collection and platform migrations while maintaining data accuracy• Achieved data acquisition, segmentation, and advanced analysis with Python, Tkinter, Webbrowser, Selenium, Kivy, among others

• Led building a fuzzy logic system to perform payee name and record information matching to avoid transaction error and fraud• Developed unit test cases to improve the code coverage of a data retrival tool to almost 80%• Tools: Java, SpringBoot and Microservice architecture, Python, Fuzzywuzzy

• Trained on Machine Learning Algorithms, ResNet, VGG-16, and other Deep Learning architectures by NUS faculty• Built a Random Forest and TFIDF model on processed text data to identify Hate Speech on Twitter• Set up Hadoop Clusters and deployed using Ambari, MapReduce, Hive, Sqoop, and Kafka for database orientation and management while implementing SQL queries with Hewlett Packard Enterprise on real-world data