Summary
Doglas Parise is a Data Scientist with a PhD and postdoc in Bioinformatics and nine years of hands-on experience turning complex biological and socioeconomic data into actionable insights using Python, R, Java, SQL and Power BI. He has built production-ready analytics pipelines and web applications—from a Django-based biological data portal delivered in under 90 days to interactive Power BI dashboards used by stakeholders. His work at national institutions (Ministry of Health, Embrapa) supported genomic surveillance and CRISPR-Cas experiment optimization, producing reproducible targets and enabling decentralized lab autonomy across Brazil. Comfortable across the stack, he combines data engineering, visualization and Linux server administration to automate large-scale analyses and improve reliability. Now at Easy Pallet, he applies bioinformatics rigor to commercial data challenges, blending research-grade methods with pragmatic software development. Outside core projects he actively documents and shares tools on GitHub, reflecting a habit of rapid prototyping and clear technical communication.
9 years of coding experience
7 years of employment as a software developer
Fédération Internationale de l'Art Photographique
Teaching degree Degree in Computing, Teaching degree Degree in Computing at Unijuí - Universidade Regional do Noroeste do Estado do Rio Grande do Sul
Post-doctorate Bioinformatics, Post-doctorate Bioinformatics at Universidade Federal de Minas Gerais
Técnico em Informática Tecnologia da Informação, Técnico em Informática Tecnologia da Informação at Colégio Concórdia
Portuguese, English, Spanish