Seda Arat is a computational toxicologist and data scientist with over a decade of experience translating complex biological data into actionable safety insights for pharma and academia. At Pfizer she leads graph-based tooling and machine learning efforts to predict safety signals and inform cross-functional decision-making, including work on mRNA vaccine-associated myocarditis risk and partnerships evaluating AI knowledge graphs. Her background—PhD in Applied Mathematics and hands-on roles from wet-lab experiments to building lab information management systems—lets her bridge biology, modeling, and software development effectively. Known for driving interdisciplinary projects, she combines rigorous quantitative methods with practical deployment experience to deliver enterprise-level predictive tools. Less obvious: she has repeatedly turned raw experimental data (ChIP-Seq, Affinity-Seq, phenotypic assays) into production-ready models and web tools, reflecting a rare end-to-end execution capability.
12 years of coding experience
4 years of employment as a software developer
Bachelor of Science (B.S.), Mathematics, Bachelor of Science (B.S.), Mathematics at Ankara Üniversitesi
Doctor of Philosophy (Ph.D.), Applied Mathematics, Doctor of Philosophy (Ph.D.), Applied Mathematics at Virginia Tech
Master of Engineering (M.Eng.), Computer and Information Technology, Master of Engineering (M.Eng.), Computer and Information Technology at University of Pennsylvania
Software Carpentry introduction to SQL for novices.
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Seda Arat - Computational Toxicologist Data Scientist