Genomics Analyst

This is a fully remote position, open to applicants in North Carolina.

📋 Description

• Process and perform quality assurance checks on metabolomics, proteomics, and/or data produced by commercial providers or university laboratories.

• Clean, filter, normalize, assess missing data, and evaluate batch effects within omics datasets.

• Implement and troubleshoot workflows that convert raw instrument data into quantified metabolite or protein data.

• Develop, maintain, and document reproducible processing and analysis workflows.

• Generate analysis-ready datasets, quality-control summaries, and data dictionaries.

• Coordinate data deliveries with laboratory and data management partners.

• Validate data, reconcile sample identifiers and metadata, harmonize datasets across batches or studies, and resolve data quality issues.

• Conduct exploratory and statistical analyses under the guidance of project investigators.

• Support the integration of metabolomics and proteomics data with other omics, clinical, phenotype, and environmental data.

• Assist with genomic analyses, including genotype data quality control and imputation, genome-wide association studies, and protein or metabolite quantitative trait locus mapping.

• Prepare tables, figures, methods descriptions, and technical reports.

• Contribute to manuscripts and communicate processing decisions and analytical results to multidisciplinary teams.

• Provide support for proposal development with input on technical sections, analytical approaches, workflows, and resource requirements.

⛳️ Requirements

• Master’s degree in Bioinformatics, Computational Biology, Biochemistry, Genetics, Statistics, or a related field, with 1 year of pertinent work experience.

• Experience managing large biomedical datasets, validating sample and feature metadata, and analyzing high-dimensional data.

• Hands-on experience in processing metabolomics, proteomics, and/or other omics data, including raw instrument data.

• Strong understanding of platform-specific quality control, preprocessing, and the generation of analysis-ready datasets.

• Working knowledge of bioinformatics tools and statistical methods for omics data processing, analysis, visualization, and biological interpretation.

• Foundational knowledge of human genetics and genomics, including genetic variation, genome builds and annotation, linkage disequilibrium, population structure and genetic ancestry, and common genomic data formats such as VCF, PLINK, FASTQ/BAM.

• Proficiency in R and/or Python, including writing clear, reusable, and well-documented code.

• Experience working in a Unix/Linux environment.

• Strong oral and written communication skills.

• Ability to collaborate respectfully and effectively with colleagues across various disciplines and research teams.

• Capacity to manage multiple tasks simultaneously.

• Must be legally authorized to work in the United States and must not require current or future sponsorship for employment visa status.

• Preferred: proficiency in high-performance computing and/or cloud computing environments, particularly AWS or Microsoft Azure.

• Preferred: experience with commercial proteomics platforms such as Olink and mass spectrometry-based metabolomics or proteomics workflows.

• Preferred: experience with metabolomics and proteomics, cross-study harmonization, multi-omics integration, or pathway and enrichment analyses.

• Preferred: experience with genetic analyses, including genotype quality control and imputation, GWAS, QTL mapping, DNA methylation array processing, or RNA-seq analysis, using tools such as PLINK, SAIGE, or Bioconductor packages.

• Preferred: experience utilizing version control such as Git and workflow management tools.

• Preferred: experience with human subjects research data.

🏝️ Benefits

• Generous paid time off policy.

• Merit-based annual increases.

• Bonus opportunities.

• Robust recognition program.

• Competitive range of insurance plans, including health, dental, life, and both short-term and long-term disability.

• Retirement savings program such as a 401(k) plan.

• Paid parental leave for all parents.

• Financial assistance with adoption expenses or infertility treatments.

• Financial reimbursement for education and developmental opportunities.

• Employee assistance program.

• Additional offerings to support a healthy work-life balance.