My work as a Data Scientist has focused on the development of a Spark-enabled analytical environment capable of processing diverse biological, chemical, and public health related datasets to generate integrated predictive models. Before that, the focus of my graduate and post-graduate research was to use computational tools to understand and predict the interplay between genes, environment, and phenotype. Specifically, as a doctoral researcher I examined the functional patterns associated with gene retention, finding environmental influence to be crucial in shaping the architecture of the eukaryotic genome. As a postdoctoral researcher, I used machine learning to perform in silico drug activity screening, directly confirming my predictions experimentally.