#001
STEM OPT Eligible
NGS & Python Specialist
MS Bioinformatics
GitHub Audited by STL-BCB
MVC Compliant
Privacy Protocol: Direct repository links are withheld to protect candidate identity. Code samples available upon interview request.
Technical Stack
Python
Nextflow
Docker
AWS
R
GATK
Domain Expertise
Oncology
Genomics
Variant Calling
Professional Summary
Computational biologist with deep expertise in building automated NGS analysis pipelines. Thesis focused on somatic variant calling in tumor-normal paired samples. Proven ability to deploy reproducible workflows using containerization and cloud infrastructure.
Technical Capabilities
Pipeline Development
- Built an automated variant calling pipeline processing 500+ samples on AWS Batch
- Implemented QC metrics dashboard using MultiQC and custom Python scripts
- Experience with both germline and somatic variant calling workflows
Infrastructure
- Proficient in containerizing bioinformatics tools with Docker
- Deployed Nextflow pipelines on AWS Batch and local HPC clusters
- Version control with Git; CI/CD experience with GitHub Actions
Domain Knowledge
- Oncology: Tumor-normal variant calling, driver gene identification
- Genomics: WGS, WES, targeted panel analysis
- Data Formats: FASTQ, BAM/CRAM, VCF, BED
Education
Master of Science in Bioinformatics
Saint Louis University, 2024
Verification Status
This candidate has been verified by the STL Bio-Compute Collective:
- GitHub repository audit: Passed
- Containerization check: Dockerfile present
- Workflow manager: Nextflow confirmed
- Code reproducibility: README with execution instructions
Interested in this Candidate?
Reference ID: #001
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