Jacob is a Senior Data Scientist for Bright.com, a hiring solution that leverages data science and engineering to move the labor market faster. Jacob was trained in integrative and computational neuroscience, and received his Ph.D. from UCSF. Since, he worked in a neuroimaging laboratory under Adam Gazzaley, where he investigated neural mechanisms of learning and memory and their decline during cognitive aging. It was here that Jacob honed his skills for managing and analyzing large datasets. At Bright.com Jacob focuses on python development, distributed systems, and machine learning. In addition to his academic publications, Jacob’s work has been featured in the WSJ, Tech Crunch, Mashable, The Daily Beast, Business Insider, and USA Today. He has extensive experience with research-based analyses such as time-frequency decomposition, map-reduce, adaptive linear spatial filtering, and coherence, version control (.git), NLP, and databases such as redis, MySQL, Solr, CouchDB, memcache, and Hadoop.
In this part-time course, students learn to build robust predictive models, test their validity, and clearly communicate resulting insights.