●Built a Python-based bioinformatics tool from the ground up to compare and analyze genomic and taxonomic data using network analysis techniques, including bootstrapping, correlation matrices, network statistics, and visualizations, enabling researchers to uncover complex biological relationships and pinpoint critical nodes and connections within the data.● Using Illumina NextSeq platforms suite to sequence samples.● Unit testing and debugging pipelines in Python, R, and Bash.● Utilize Python to construct a network graph with nodes representing species and edges determined by comparison and employed Combo-Seq Data Analysis (CODA) to perform differential analysis and calculate Jaccard coefficients, providing valuable insights into species relationships and similarities.● Writing algorithms using tools from pandas, scikit-learn, NumPy, and tidyverse.● Perform RNAseq Analysis to understand changes in gene expression by running statistical analyses and visualizing their differentiability using R and Python.● Annotate genomes using AUGUSTUS to predict sequences and used JBrowse to visualize the annotations.

● Developed dashboards in library software for senior management to track course material utilization during COVID, resulting in a 60% increase in usage after converting to a digital service modelupon converting to a digital service model, showing a 60% increase in usage● Improved the UX by reorganizing landing pages of various services the library offers from our program using JavaScript based on SEO and Google Analytics reports generated by the dashboards I created.

● Built and managed a data repository of customer activity using Millennium Software to create reports that management teams used to make operational decisions.● Automated data extraction processes via VBA to provide suggestions to our department for determining allocation of annual funds and resources based on patron utilization● Collaborated with the meta-data team to build the workflow for a data migration of a software that was desktop located to web-based, translating the service model to a more digital approach

● Collaborated with a team of researchers to collect and code over 3000 data points of participant behavior used forhypothesis testing● Utilized R to calculate p-value and statistical significance of the data to create various prediction curves used insupporting our study results● Published a report with in-depth models on findings and insights gathered during the study