Marietta, Georgia, United States
Developed cubic regression model and other models that incorporate LDA topic modeling derived categorical variables. Approved by system for risk quantification Created systemwide internal RAG chatbot. Set up knowledge bases and python based web scraping scripts to update the knowledge base Coded in Python, R, and SQL to clean large and complex datasets for different business lines across the national system. Consulted business lines to improve data collection and automation processes Created advanced interactive data visualizations with Tableau and Power BI as well as visual reports in R. Presented dashboards to senior leadership Trained interns and new employees on different databases and visualization techniques and consult them in projects that contribute to the company in the long run
Gathering large, time-series data and finding relationships between the company's claims metrics and external factors using highly advanced statistics. Built out advanced claim metrics forecast library to predict claim trends that is currently being used by the executives for hiring planning. Creating large and complex datasets that are being used to track the customer lifetime value. Manipulating datasets that are thousands of gigabytes big to build an Excel tool that makes it easier for executives to track customer lifetime value Training new analysts and supervising interns to become more familiar with forecasting and data manipulation techniques as well as gain business knowledge so that they can contribute more to the company quicker Extensive usage of SAS suite, Excel, SQL, and other advanced internally developed data mining tools
Aggregated and analyzed large Census data (up to 700,000 data points per set) on manufacturing plants and companies Used programming languages such as SAS and Stata and wrote different codes for the research team to help the analysis process Received security clearance from the government
Aggregated and analyzed large amounts of data to construct statistical models that predict the company's claims and financial trends in the future Researched and presented the effects natural disasters have on the company's financial growth to the senior leadership Used SAS and Excel to construct advanced programs that construct forecasting models for applicable financial data sets