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Bioinformatics Polygenic Risk Gwas Jobs (NOW HIRING)

Scisco Genetics

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Bioinformatics Scientist / Genomic Data Analyst

Seattle, WA · On-site

$95K - $115K/yr

... GWAS, eQTL analysis, or rare variant analysis ... Familiarity with population structure, ancestry inference, polygenic risk scores, or fine-mapping ...

The University of Miami

Asst. Scientist

Miami, FL · On-site

... polygenic risk score derivation and validation, etc. • Provides statistical expertise in data ... methods. • Bioinformatic Analysis (Advanced): Experienced in gene differential expression ...

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Bioinformatics Polygenic Risk Gwas information

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$59.5K

$94.5K

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How much do bioinformatics polygenic risk gwas jobs pay per year?

As of Jun 7, 2026, the average yearly pay for bioinformatics polygenic risk gwas in the United States is $94,474.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,500.00 and $129,500.00 per year, depending on experience, location, and employer.

What is a Bioinformatics Polygenic Risk GWAS specialist?

A Bioinformatics Polygenic Risk GWAS specialist is a professional who applies computational and statistical methods to analyze genome-wide association studies (GWAS) data in order to assess polygenic risk scores. These experts help identify genetic variants across the genome that contribute to the risk of complex diseases by integrating large-scale genetic data. Their work supports advances in personalized medicine by enabling more accurate prediction of disease risk based on an individual's genetic makeup.

How does a Bioinformatics Polygenic Risk GWAS specialist typically collaborate with geneticists and clinicians in a research setting?

Bioinformatics specialists working on Polygenic Risk GWAS projects frequently collaborate with geneticists to design studies, interpret GWAS findings, and identify meaningful genetic variants. They also work closely with clinicians to translate polygenic risk scores into actionable insights for patient care or disease prediction. Effective communication and teamwork are essential, as the role often involves explaining complex statistical results and integrating diverse datasets to support interdisciplinary research goals.

What are the key skills and qualifications needed to thrive as a Bioinformatics Polygenic Risk GWAS specialist, and why are they important?

To thrive as a Bioinformatics Polygenic Risk GWAS specialist, you need a strong background in genetics, statistics, and computational biology, typically supported by an advanced degree in bioinformatics or a related field. Proficiency with programming languages (such as Python or R), statistical genetics software (like PLINK or GCTA), and experience analyzing large-scale genomic datasets are essential. Attention to detail, problem-solving ability, and effective communication skills help you interpret complex data and collaborate with multidisciplinary teams. These skills are vital for producing reliable genomic insights that can inform research and clinical decisions.

What is the difference between Bioinformatics Polygenic Risk Gwas vs Bioinformatics Data Analyst?

AspectBioinformatics Polygenic Risk GwasBioinformatics Data Analyst
Required CredentialsDegree in Bioinformatics, Genetics, or related field; experience with GWAS and statistical analysisDegree in Data Science, Statistics, or related; proficiency in data analysis tools
Work EnvironmentResearch labs, academic institutions, biotech companiesCorporate, healthcare, or research organizations
Industry UsageGenetics research, personalized medicine, disease risk predictionData interpretation, reporting, and visualization across industries

Bioinformatics Polygenic Risk Gwas specialists focus on genome-wide association studies to identify genetic risk factors, requiring specialized genetic and statistical expertise. In contrast, Bioinformatics Data Analysts handle broader data sets, providing insights through data processing and visualization. While both roles involve data analysis skills, their focus areas and industry applications differ significantly.

Infographic showing various Bioinformatics Polygenic Risk Gwas job openings in the United States as of May 2026, with employment types broken down into 100% Full Time. Highlights an 89% In-person, and 11% Remote job distribution, with an average salary of $94,474 per year, or $45.4 per hour.
Bioinformatics Scientist / Genomic Data Analyst

Bioinformatics Scientist / Genomic Data Analyst

Scisco Genetics

Seattle, WA • On-site

$95K - $115K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 5 days ago

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Job description

We are seeking a highly trained Bioinformatics Scientist with a PhD or equivalent research experience in bioinformatics, computational biology, genetics, genomics, immunology, or a closely related field. The ideal candidate will have strong experience analyzing genomic sequence data and a deep interest in the genetic basis of human immune response.

This role will focus on the analysis and interpretation of genomic, transcriptomic, and/or immune-related sequence datasets to help identify genetic variation, molecular pathways, and biological mechanisms associated with human immune function, immune response, disease susceptibility, vaccine response, inflammation, autoimmunity, infection, or related phenotypes.


Key Responsibilities

The selected candidate will:

  • Analyze high-throughput genomic sequence data, including whole-genome sequencing, whole-exome sequencing, targeted sequencing, and related datasets.
  • Develop, implement, and optimize bioinformatics pipelines for sequence data processing, quality control, variant calling, annotation, and downstream interpretation.
  • Investigate genetic contributors to human immune response, including HLA variation, immune receptor loci, cytokine pathways, host-pathogen response, or other immunogenetic features.
  • Integrate genomic data with clinical, phenotypic, immunological, or functional datasets.
  • Interpret results in a biologically meaningful context and communicate findings to interdisciplinary teams.
  • Prepare reports, figures, manuscripts, grant materials, or presentations summarizing analytical methods and scientific findings.
  • Collaborate with scientists, clinicians, computational biologists, immunologists, and other stakeholders.


Required Qualifications

  • PhD in bioinformatics, computational biology, human genetics, genomics, immunology, biostatistics, or a related discipline.
  • Demonstrated experience analyzing genomic sequence data.
  • Strong understanding of human genetics and genomic variation.
  • Familiarity with immune response genetics, immunogenomics, host-pathogen genetics, vaccine response genetics, autoimmunity, inflammatory disease, or related areas.
  • Proficiency in programming and data analysis using tools such as Python, R, Bash, Nextflow, Snakemake, or similar platforms.
  • Experience working in Linux/Unix computing environments and with high-performance computing or cloud-based analysis systems.
  • Familiarity with standard bioinformatics tools and file formats, such as FASTQ, BAM/CRAM, VCF, GTF/GFF, BED, BCFtools, GATK, PLINK, STAR, HISAT2, Salmon, Seurat, or related tools.
  • Ability to work independently, manage complex datasets, and document analytical workflows clearly.


Preferred Qualifications

  • Experience with HLA typing, immune repertoire sequencing, single-cell immune profiling, GWAS, eQTL analysis, or rare variant analysis.
  • Familiarity with population structure, ancestry inference, polygenic risk scores, or fine-mapping methods.
  • Prior publications or demonstrated research contributions in immunogenetics, infectious disease genetics, autoimmune disease genetics, cancer immunology, vaccine response, or related fields.
  • Experience with reproducible workflow development, containerization, Git-based version control, or cloud platforms such as AWS, Google Cloud, or Azure.


Desired Skills and Attributes

  • Strong analytical and problem-solving skills.
  • Excellent scientific communication skills.
  • Ability to collaborate across computational, biological, and clinical teams.
  • Careful attention to data quality, reproducibility, and documentation.
  • Intellectual curiosity and interest in the genetic determinants of human immune function.



Company Description

Scisco Genetics, a Seattle-based biotechnology company, specializes in next-generation sequencing (NGS) services and products for genotyping complex immune gene systems, including HLA, KIR, MICAB, FCGR, and IGHG. Founded and led by Dr. Daniel Geraghty, whose research at the Fred Hutchinson Cancer Research Center focuses on immune genetics, the company offers tools like the ScisGo product and Version 6 NGS HLA Typing Kit for high-resolution, accurate genotyping, supporting applications such as hematopoietic cell transplants and precision medicine.