Data Scientist and Bioinformatics Researcher with expertise in machine learning, statistical modeling, and large-scale data analysis. I specialize in transforming complex biological and genomic datasets into actionable insights through predictive analytics, data visualization, and reproducible computational workflows.

My experience spans data science, genomics, and AI-driven analytics, with a strong focus on extracting meaningful patterns from high-dimensional datasets and communicating results effectively to support data-driven decision-making.

• Machine Learning & Predictive Modeling
• Statistical Analysis & Experimental Design
• Data Visualization & Storytelling
• Python (Pandas, NumPy, Scikit-learn, TensorFlow)
• R (tidyverse, ggplot2, Bioconductor)
• SQL & Database Analytics
• Big Data & High-Performance Computing (HPC)
• Reproducible Pipelines (Nextflow, Snakemake)
• Genomics, Multi-omics & Computational Biology

• Applied Machine Learning and AI
• Predictive Analytics and Feature Engineering
• Data Mining and Pattern Discovery
• Explainable AI (XAI)
• Business Intelligence and Data Visualization
• MLOps and Reproducible Data Science Workflows

• Machine learning models for predicting complex biological traits.
• Multi-omics data integration and predictive analytics.
• GWAS, CNV, and population genomics data analysis.
• End-to-end data science pipelines for large-scale datasets.
• Interactive dashboards and visual analytics for scientific and business applications.

I'm always interested in collaborating on data science, machine learning, AI, and computational biology projects. Feel free to explore my repositories and connect!