My background includes over a decade of experience as a neuroscientist, data scientist, and software developer, holding a PhD in neuroscience and a degree in teaching in higher education. I am eager to contribute to the industrial sector, applying my skills in data science, artificial intelligence, and product development to drive company growth. In academia, my research program improves the methodological practices of neuroscience by leveraging artificial intelligence. Notable contributions include validating EEG dataset augmentation through generative modelling, automating multiple stages of the empirical research process, and confirming the efficacy of symbolic regression in recovering computational models of cognition. Further, I developed and collaborated on open-source Python packages that were essential for each of these projects — specifically, EEG-GAN, AutoRA, and Equation-Scraper, respectively. The success of my research program is demonstrated through my 23 publications (1 senior author, 9 first author), 19 awards totalling $214,213, and an NSERC-Mitacs Grant awarded at $60,000. In industry, my projects centered on developing biometric integration and analysis software, neurofeedback protocols, and data quality assessments. For instance, I designed an application that detects, connects, and streams three wearable biometric devices, allowing users to concurrently visualize, record, and transmit raw data with computed metrics. A different project comprised of creating a brain-computer interface to control technology using mobile EEG. In other work, I developed an open-source application for evaluating EEG recordings to assess the quality of different devices. These experiences involved working independently and in teams across six companies as well as with over 20 wearable biometric devices within Python, Matlab, and R.