Renata Schama

Background

About Renata Schama

I am a curiosity-driven, self-motivated computational biologist with 10 years of experience who firmly believes that working collaboratively achieves higher results. As a data-driven scientist, my background in evolutionary biology, with expertise in genomics, phylogenetics, metagenomics, and genetic variability, makes me feel comfortable with open-ended questions and analyzing large amounts of data to obtain results. A cross-functional collaborator that has worked with 6 different institutions, spanning 9 laboratories in 3 continents. These collaborations have generated 14 publications in peer-reviewed journals and a book chapter, the discovery of 2 new species, and helped implement and guide vector control strategies in Brazil. As a fast learner and critical thinker, I thrive working in interdisciplinary teams and learning from different stakeholders. I find that joining technical and operational expertise is the way to solving complex problems. Highly adaptable and comfortable working in a fast-paced environment. As a CFO of an importing/exporting textile company I helped implement new processes that ensured the company’s financial stability in the global market, surpassing the difficulties of an ever-changing economic landscape of a developing country with a fluctuating exchange rate. Good at communicating through storytelling with the ability to present scientific data and concepts to a broad audience, as evidenced by giving 5+ lectures to non-experts, being responsible for coordinating and teaching 8 graduate courses and doing volunteer work teaching the public on how to control mosquito vectors. Mentorship expertise with the ability to design and interpret study results related to bioinformatics and statistical analysis, as demonstrated by supervising 6 graduate theses in Computational Biology. Brazilian scientists are entrepreneurial and problem solvers by nature and have to be passionate about what they do to obtain results with low resources. My publications: ORCID: Google Scholar: https://scholar.google.com.br/citations?hl=pt-BR &