Semiramis Castro is a Data Scientist with 10 years of experience building data analysis and visualization tools in Python and R, currently applying her skills at Kantar after completing a PhD in biomedical sciences. Her research at UNAM focused on optimizing large-scale scientific workflows—turning processes that once took 30 days into sub-minute automated pipelines via parallel processing and custom scripting. She combines statistical techniques (PCA, clustering, similarity indices) with network analysis and polished visual reporting (ggplot2, matplotlib) to deliver actionable insights and reproducible results. Based in Mexico City, she bridges academia and industry, with a strong emphasis on automation and performance that extends from Bash and Perl scripting to production-ready Python tools. Her public work and code are available on GitHub and her personal site, reflecting a pragmatic, research-driven approach to data engineering and visualization.
Scripts for data visualization for practice with python and R libraries
Contributions:8 pushes, 2 branches in 2 years 5 months
polarspythonbokehplotsholoviews
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