• Optimized integral algorithm for enhanced effectiveness and computational speed, through the use of large-scale survival analysis simulations within high-performance computing environments.• Created an R Shiny application to execute the algorithm on-demand and provide detailed diagnostics on its performance and results.

• Utilized MATLAB for data analysis, implementing wavelet spectra on signals, and extracting model features• Implemented a range of supervised learning classification algorithms, including logistic regression, k-nearest neighbors (KNN) and Support Vector Machines (SVM), to evaluate predictive accuracy• Demonstrated expertise in reviewing, summarizing, and writing research articles focused on predicting ADHD and Parkinson's disease

• Imported, cleaned, and analyzed large client data sets in order to draw insights on retirement plan assets/liabilities• Developed and delivered actuarial valuations and de-risking strategies, presenting findings to senior consultants for informed decision-making.

- Intensive exploration into the fundamentals of Data Science using the R programming language in DataCamp- Analyzed athlete data in order to construct the best possible fantasy teams for a particular sport

• Aided in development and testing of in-house model management software intended to streamline model change control process • Constructed a fully automated Model Comparison report through VBA that analyzes and displays file differences amongst different POLY Models.• Explored the possible uses of python in AWS to aid in file management, storage, and connections to redshift and aurora