Bioinformatics Scientist - III (Senior)

About the role

We are a national staffing firm currently seeking a Senior Bioinformatics Scientist for a prominent client. The position offers $95‑106/hr, a 23‑month duration, Monday‑Friday schedule, and is located onsite in Cambridge, MA within the Data and Genome Sciences – Precision Genetics department. The role requires a Ph.D. and 5+ years of genetic data analysis experience.

Responsibilities

• Analyze and integrate large-scale human genetic, genomic, and multi-omics datasets.
• Perform genetic data QC, variant analysis, annotation, GWAS/PheWAS, QTL analysis, and population genetics.
• Develop and validate machine learning models for variant prediction, patient stratification, and biomarker discovery.
• Integrate genetic data with transcriptomic, proteomic, epigenomic, single-cell, and spatial datasets.
• Work with large external datasets and resources such as UK Biobank, gnomAD, GTEx, ClinVar, and GWAS Catalog.
• Develop reproducible, version-controlled workflows and document analysis methods and results.
• Utilize HPC systems and AWS Cloud Computing to support large-scale analyses.

Qualifications

• Ph.D. in Genetics, Genomics, Statistical Genetics, Computational Biology, or a related field.
• 5+ years of experience in human genetic/genomic data analysis.
• Strong knowledge of statistical genetics, including variant analysis, GWAS, QTL mapping, population genetics, and genomic annotations.
• Demonstrated experience applying machine learning to high-dimensional biological data.
• Hands-on experience with multi-omics data integration.
• Proficiency in R, Python, and Bash.
• Experience with HPC systems and AWS Cloud Computing, including IAM and S3.
• Experience with tools such as PLINK, GATK, bcftools, VEP/ANNOVAR, REGENIE, SAIGE, and/or related genomic analysis tools.
• Strong communication, organization, and problem-solving skills.
• Preferred: Experience with large-scale biobank data such as UK Biobank, All of Us, or FinnGen.
• Preferred: Experience with deep learning for genomics.
• Preferred: Experience with single-cell or spatial transcriptomics.
• Preferred: Pharmaceutical/biotechnology experience supporting drug target identification or biomarker discovery.
• Preferred: Familiarity with Nextflow, Snakemake, Docker, or Singularity.