Data Scientist

Jared H. Buss

Belleville, IL • 618-***-**** • **********@*****.***

Professional Summary

Bioinformatics Scientist with over 3 years of experience in transcriptomic and multi-omics data analysis, specializing in neurodegenerative and vascular disorders. Skilled in developing reproducible analysis pipelines, data visualization tools, and machine learning models for biomedical research. Strong technical foundation in R, Python, and Shiny, with a proven publication record and a passion for creating user-friendly scientific tools.

Education

Saint Louis University — St. Louis, MO

M.S. in Bioinformatics and Computational Biology • May 2022

Loyola University Chicago — Chicago, IL

B.S. in Molecular Biology • May 2018

Professional Experience

Washington University School of Medicine — Department of Neurology • St. Louis, MO

Staff Scientist • Oct 2023 – Present

Led statistical modeling and visualization of scRNA-seq and spatial RNA-seq data using R and the xenium explorer for stroke-related research

Developed scalable R pipelines executed via Snakemake for efficient and reproducible analysis involving both R and Python (cellphone DB Python application)

Collaborated with multidisciplinary teams to generate publication-quality figures and use deep learning to identify neural networks for interpretation of neurological data

AbbVie Genomics Research Center — Computational Biology Neuroscience • Remote

Bioinformatics Data Analyst II • Nov 2022 – May 2023

Analyzed single-cell RNA-seq data to perform trajectory and differential expression analysis using Seurat and Monocle

Developed an interactive Shiny app to visualize gene expression across Alzheimer’s disease progression

Automated and documented workflows using R and Python scripts to support reproducibility in data analysis

Washington University — Neurogenomics and Informatics Center • St. Louis, MO

Bioinformatics Data Analyst • May 2021 – Nov 2022

Created a Shiny-based tool for deconvolution of bulk RNA-seq data using single-cell references

Engineered a machine learning model for cell type identification leveraging multi-omics data and Bioconductor packages

Performed ambient RNA contamination correction in droplet-based scRNA-seq data pipelines

Publications

Brain high-throughput multi-omics data reveal molecular heterogeneity in Alzheimer’s disease. PLOS Biology, 22(3):e3002607. https://doi.org/10.1371/journal.pbio.3002607

Ambient RNA from CSF to capture brain cell-type signatures in AD and other neurodegenerative diseases. Alzheimer's & Dementia, https://doi.org/10.1002/alz.077297

Cross-omics integration analysis reveals synaptic dysregulation across brain regions at later stages of Alzheimer’s disease. Alzheimer's & Dementia. https://doi.org/10.1002/alz.077100

Exploring the transcriptome of human blood clots via spatial transcriptomic analysis. medRxiv. https://doi.org/10.1101/2022.12.10.22283295

Technical Skills

Languages: R, Python; familiar with Java, C++, SQL

Tools & Frameworks: Seurat, Snakemake, CellRanger, STAR, Salmon, Monocle, Shiny, CellphoneDB, hdWGCNA

Data Visualization: ggplot2, Shiny, Affinity Designer, PowerPoint, Adobe Acrobat

Pipelines & Platforms: SRA, Bioconductor, GitHub, Shiny Server

References

Oscar Harari • Chair, Department of Neurology, Ohio State University • *****.******@*****.***

Ricardo D'Oliveira Albanus • Postdoctoral Research Associate • ********@*****.***

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