K*****s
About Candidate
Karl is a Magna cum Laude graduate of the degree Bachelor of Science in Statistics from Central Luzon State University, with strong expertise in data analysis, statistical modeling, and visualization using R, Python, and SAS. He has hands-on experience working with high-dimensional datasets and building end-to-end statistical and predictive modeling pipelines, with particular research interest in missing data analysis, genomic prediction, and advanced forecasting methods. Karl effectively communicates complex analytical results into clear, actionable insights through academic and client-oriented projects. He also demonstrated good leadership skills through active involvement in various university organizations and participation in international academic and cultural exchanges. Driven by evidence-based decision-making, he is eager to apply data-driven solutions in research, healthcare, and policy-focused environments.
Nationality
Location
Education
The program is designed for students who are interested in Statistics and Data Science. It equips students with the fundamental knowledge and training necessary to develop their conceptual, computational, mathematical, and communication skills for data acquisition and management, data analysis and visualization techniques, and effective communication of results to a diverse group of stakeholders.
Work & Experience
Responsible for the analysis of genomic and proteomic datasets to identify RNA-binding sites, supporting project objectives related to RNA–protein interaction studies. Performed whole-genome sequencing data processing and variant discovery using Bash, Python, and R, resulting in the identification of 7,038 SNPs and 969 InDels in Enterococcus faecium. Assisted in conducting minor laboratory procedures necessary for sample preparation and data validation. Developed and maintained an RNA-binding protein database to systematically store, organize, and support downstream bioinformatics and functional analyses.
Served as a freelance Statistician to student researchers.
