Tulio Baars is a statistical programmer and data scientist with 11 years of experience applying physics-based thinking and machine learning to real-world problems across healthcare, marketing, and fintech. Trained in Applied Physics (UFSC) and advanced R and data science programs at Johns Hopkins, he has run epidemiological simulations, developed production ML pipelines, and implemented CDISC-aligned statistical workflows for clinical trials at Syneos Health and Roche. He founded epidemic Labs to fuse AI and biological simulation for more effective advertising, and earlier built campaign optimization, influencer-mapping systems, and custom algorithms for clients including Unilever, PepsiCo and Google Brasil while at Garage IM. Tulio combines research experience with NASA/Stanford collaborations and hands-on engineering—R, Python, TensorFlow, D3.js and cloud deployment—bridging exploratory analysis to regulatory-ready reports. Notably, he moves fluidly between academic research and production operations, turning complex simulations and unstructured data into actionable business and clinical insights. Based in Greater Florianópolis, he brings a pragmatic multidisciplinary approach to statistical programming and data-driven strategy.
11 years of coding experience
11 years of employment as a software developer
Ciências da Computação, Computer Science, Ciências da Computação, Computer Science at Universidade Federal de Santa Catarina
Johns Hopkins University
Architecting with Google Cloud Platform Specialization, Computer Systems Networking and Telecommunications, Architecting with Google Cloud Platform Specialization, Computer Systems Networking and Telecommunications at Google Cloud Certified
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