Bioinformatics Analyst

This is a remote position.

• Process and analyze genomic and other omics datasets (for example, whole‑genome, whole‑exome, RNA‑seq, or similar assays), including alignment, quality assessment, variant detection, and annotation.
  
  
• Develop, document, and maintain reproducible analysis pipelines using modern workflow or pipeline tools and scripting languages.
  
  
• Implement best practices for data quality control, including monitoring run performance, detecting technical issues, and proposing corrective actions.
  
  
• Integrate data from multiple sources, harmonize formats and metadata, and prepare analysis‑ready datasets.
  
  
• Work with common bioinformatics tools and file formats (e.g., FASTQ, BAM/CRAM, VCF, BED, GFF/GTF) in a Unix/Linux environment.
  
  
• Develop and execute exploratory analyses, including cohort‑level summaries, visualization of key metrics, and interpretation of variant and gene‑level results.
  
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• Prepare clear, well‑structured reports, figures, and presentation materials describing methods, assumptions, and findings for collaborators with diverse backgrounds.
  
  
• Contribute to the evaluation and adoption of new algorithms, tools, and workflows in bioinformatics and data analysis.
  
  
• Collaborate with other team members on study design, analysis plans, timelines, and prioritization of tasks.
  
  

• Graduate degree or equivalent experience in Bioinformatics, Computational Biology, Genomics, Computer Science, Statistics, or a related field.
  
• Practical experience with next‑generation sequencing data analysis (such as WGS, WES, or RNA‑seq), including quality control, alignment, and variant or expression analysis.
  
• Proficiency in at least one scripting language commonly used in bioinformatics (e.g., Python or R), and familiarity with relevant scientific or data‑analysis libraries.
  
• Experience working in Unix/Linux environments, including shell scripting and command‑line tools.
  
• Familiarity with standard genomics file formats and commonly used open‑source tools for sequence data processing and variant analysis.
  
• Exposure to workflow or pipeline management tools (such as Nextflow, Snakemake, CWL, WDL, or comparable systems), and an understanding of reproducible analysis practices.
  
• Strong organizational skills, attention to detail, and the ability to manage multiple analysis tasks in parallel while meeting agreed timelines.
  
• Clear written and verbal communication skills, including the ability to describe analytical approaches and results to non‑specialists.
  

• Experience with clinical or population‑based genomic datasets in any disease area.
  
• Familiarity with high‑performance or distributed computing environments used for computational biology workloads.
  
• Experience building and maintaining ETL (extract–transform–load) workflows and working with relational or NoSQL databases.
  
• Background in statistics, statistical genetics, or related quantitative disciplines.
  
• Contributions to shared code bases or open‑source projects in bioinformatics or data analysis.
  
• Experience generating visualizations or dashboards for scientific data using tools such as R Shiny, Plotly, Dash, or similar frameworks.
  

• Comfortable working in a collaborative environment with researchers, analysts, and software professionals.
  
• Able to estimate effort, communicate progress, and flag risks or issues early.
  
• Curious and willing to learn new analytical methods, tools, and technologies.