Anna Gabriela Vargas

I’m a Data Scientist with a strong foundation in machine learning, statistical modeling, and analysis of high-dimensional datasets. I build reproducible data workflows and develop predictive models that translate complex results into clear, impactful decisions.

At BioXpedia A/S, I delivered end-to-end data analysis on high-dimensional datasets, including data preprocessing and cleaning, quality control, normalization, and statistical modeling. I also developed and optimized reproducible R pipelines, improving efficiency, scalability, and reliability across client-driven projects.

Previously, as a Research Assistant in the Forensics & Molecular Biology department at IDEA, I supported sequencing operations and performed Sanger sequencing for forensic and diagnostic applications. I conducted paternity testing analyses and prepared technical reports for clinical and legal contexts while supporting standardized laboratory workflows to ensure reproducibility and data quality.

My MSc in Bioinformatics at Aarhus University strengthened my practical ML and deep learning skills through work on unsupervised learning for patient data, as well as deep learning for image classification tasks. I’m especially motivated by projects that demand robust modeling, strong quality control, and scalable, high-performance data science workflows.