Senior Bioinformatics Scientist - III (Genomics)

Location: Onsite in Cambridge, Massachusetts; fully remote work is not available.

Salary: $213,800–$220,500 annually.

Company

hirify.global provides staffing and contractor placement services for technical and scientific roles.

What you will do

• Query, acquire, harmonize, and quality-control genetic, genomic, and multi-omics datasets from public databases and large biobanks.
• Perform genotype imputation, variant calling, genomic annotation, GWAS, PheWAS, rare-variant testing, fine-mapping, colocalization, polygenic scoring, and Mendelian randomization.
• Conduct eQTL, sQTL, and pQTL analyses and investigate population variation, ancestry, linkage disequilibrium, and relatedness.
• Develop, benchmark, and validate machine learning models for variant-effect prediction, patient stratification, biomarker prediction, and treatment-response prediction.
• Integrate transcriptomics, epigenomics, proteomics, single-cell, and spatial omics data to generate biological and disease insights.
• Create documented, version-controlled, and reproducible workflows for computational analysis.

Requirements

• Ph.D. required in genetics, genomics, statistical genetics, computational biology, or a related field; candidates whose highest degree is a BS or MS are not eligible.
• At least 5 years of experience in genetic data analysis.
• Strong knowledge of variant analysis, GWAS, QTL mapping, population genetics, genomic annotation, and statistical genetics.
• Experience applying machine learning to high-dimensional biological data, including feature engineering, model selection, validation, cross-validation, and bias control.
• Hands-on experience integrating genetic data with transcriptomics, proteomics, and epigenomics.
• Proficiency in R, Python, and Bash, plus experience with high-performance computing, AWS IAM and S3, and reproducible analysis practices.

Nice to have

• Experience with large biobank datasets such as UK Biobank, All of Us, FinnGen, or electronic health record-linked cohorts.
• Experience with deep learning for genomics, sequence-based models, or variant-effect prediction.
• Familiarity with single-cell and spatial transcriptomics, drug target identification, target validation, or biomarker discovery.
• Experience with Nextflow, Snakemake, Docker, or Singularity.

Culture & Benefits

• Work independently and collaboratively in a dynamic research environment.
• For temporary assignments lasting 13 weeks or longer, medical, dental, vision, 401(k), and statutory sick pay may be available.
• Reasonable accommodations are provided during the employment process.