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Full Stack Bioinformatics Scientist; Animal Genomics

Job in Austin, Travis County, Texas, 78716, USA
Listing for: Scismic
Full Time position
Listed on 2026-03-10
Job specializations:
  • IT/Tech
    AI Engineer, Data Scientist
  • Research/Development
    Data Scientist
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: Full Stack Bioinformatics Scientist (Animal Genomics)

Scismic is supporting the growth of a fast-growing biotech startup focusing on animal genomics. They are seeking a Bioinformatics Scientist to transform raw sequencing data into high-impact biological insights.

What You’ll Do
  • Pipeline Architecture: Build and manage end-to-end WGS and low-pass sequencing pipelines (QC, alignment, variant calling, and annotation).
  • Genomic Dataset Development: Construct and refine species-specific genotype datasets, starting with equine and expanding across multiple large animal models.
  • Statistical Analysis: Lead association studies (GWAS) and population genetics analyses to identify actionable genetic targets.
  • Reproducible Science: Maintain scalable, containerized workflows using Nextflow or Snakemake within cloud environments.
  • Predictive Modeling: Develop custom ML/AI frameworks to support trait modeling, animal valuation, and performance forecasting.
Who You Are
  • Technical Expert: Strong background in NGS data analysis, specifically whole-genome sequencing (WGS) and variant discovery.
  • Coder: Proficient in Python and/or R, with deep comfort in Linux, HPC, or cloud computing (AWS/GCP).
  • Workflow Driven: Experience using Docker and workflow languages (WDL/Nextflow) to ensure reproducible results.
  • Analytically Minded: You enjoy the challenge of imputation, polygenic risk scores (PRS), and translating complex data into clear recommendations.
Preferred Experience
  • Direct experience in large animal genomics (equine, bovine, or porcine).
  • Background in population genetics or agricultural genomics.
  • Familiarity with building data products in a startup or rapid-growth setting.
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