Jacob Pritt is a Genomics Scientific Developer with 12 years of experience combining computational genomics, bioinformatics, and software engineering, holding a PhD in Computer Science from Johns Hopkins. He builds scalable analysis pipelines and tools—drawing on C++, R, and Python—to extract regulatory programs from time-series transcriptomics across plants, microbes, yeast fermentations, and human circadian studies. His work spans algorithm development (e.g., compression and graph-genome optimization during his PhD) to cloud-enabled production analyses on AWS, with practical experience in databases, SQL, and Git-based workflows. At Syngenta and previously as Lead Computational Scientist at Mimetics, he has translated research-grade methods into deployable solutions for real-world phenotype and stress-response questions. Colleagues find his combination of deep algorithmic rigor and hands-on engineering rare in genomics teams, and he often bridges gaps between single-cell segmentation, large-format genomic data handling, and time-series regulatory inference.
12 years of coding experience
14 years of employment as a software developer
Johns Hopkins University
Bachelor of Arts (BA), Computer Science, Bachelor of Arts (BA), Computer Science at Harvard University
Contributions:3 commits, 1 push in 2 years 6 months
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Jacob Pritt - Genomics Scientific Developer at Syngenta