Dan Nasko

San Diego, CA

Dan Nasko

Staff Data Scientist · Bioinformatics

Experienced bioinformatics and data science professional bridging complex biological datasets and actionable insight — in pharma, biotech, and beyond.

About

I'm an experienced bioinformatics and data science professional with 6+ years of industrial experience working in computational biology. I specialize in analyzing complex biological datasets to drive innovation in biotech and pharma — skilled in machine learning, statistical modeling, and programming in Python, R, and SQL. I hold a PhD in Bioinformatics and Data Science from the University of Delaware and a BSc in Pharmaceutical Product Development from West Chester University. Outside the lab, you'll find me cycling, hiking, or spending time with my dogs.

Experience
2022 – Present
Staff Bioinformatics Scientist
PacBio · San Diego & Menlo Park

Develop bioinformatics workflows for secondary analysis of NGS data across PacBio HiFi, SBB, Illumina, and Nanopore platforms. Support oncology and microbiome research; build visualizations in Python and R Markdown for variant calling performance evaluation.

2021 – 2022
Senior Data Scientist
Novozymes · San Diego & Davis

Built automated, data science-driven infrastructure for microbiome research integrating metagenomics, 16S, metabolomics, and metatranscriptomics. Led biological discovery of novel bacterial and phage probiotic candidates from human and animal gut samples.

2019 – 2021
Senior Data Scientist
Biota Technology · San Diego (Acquired by Novozymes 2021)

Applied machine learning to microbial signatures from subsurface samples to trace reservoir connectivity, assess production potential, and optimize resource management strategies in energy exploration.

Research

Rapid and robust characterization of unknown pathogenic DNA/RNA sequences.

Identifying novel CRISPR families from environmental samples.

Examining how database composition affects k-mer-based taxonomic classification over time.

Viral metagenomics pipeline and web app to explore viral diversity in environmental samples.

Shotgun metagenomic characterization of microbial communities in crop irrigation water sources.

Tool for predicting viral replication strategy via DNA polymerase analysis.

Skills
Python & Jupyter
R & ggplot2
SQL & MongoDB
Snakemake & Nextflow
Scikit-learn & Keras
Bioinformatics Pipelines
Machine Learning
Statistical Modeling
NGS Data Analysis
Metagenomics
Matplotlib & Seaborn
Viral Metagenomics