Description
Apply bioinformatics methods to support research and product development in pharmaceuticals, biotechnology, and medical informatics. Implement and optimize pipelines, databases, and algorithms to process and analyze genomic and other biological data; evaluate tools, ensure data quality, and deliver reproducible analyses and reports.
- • Recommend and implement systems, pipelines, and processes to improve bioinformatics operations.
- • Stay current with sequencing chemistries, instrumentation, and software; evaluate relevance for adoption.
- • Coordinate with R&D, clinical, and operations teams to support product and workflow improvements.
- • Partner with software engineers to configure, integrate, and improve bioinformatics tools.
- • Validate and benchmark new or updated bioinformatics software.
- • Provide and maintain statistical and computational tools for genetic analysis and gene expression studies.
- • Generate summary statistics and quality control metrics for genomic datasets.
- • Train scientists and clinicians on selecting and using bioinformatics tools and databases.
- • Improve user interfaces and documentation for bioinformatics software and databases.
- • Coordinate with lab technicians and IT staff to deploy tools across omics workflows.
- • Customize and script applications to meet project-specific analysis needs.
- • Design and maintain data models, schemas, and bioinformatics databases.
- • Create or modify web-based dashboards and tools for data access and visualization.
- • Implement and apply bioinformatics algorithms, including machine learning methods, as needed.
- • Develop reproducible pipelines and workflows tailored to research goals.
- • Aggregate and curate data for gene expression profiling, genome annotation, and structural analyses.
- • Prepare analysis reports, visualizations, and contributions to publications and presentations.
- • Integrate and query public and proprietary genomic, proteomic, and metabolomic databases.
- • Consult with researchers to define requirements, troubleshoot analyses, and recommend computational strategies.
- • Analyze large-scale sequencing, transcriptomic, and proteomic datasets for research and clinical projects.
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Last reviewed: Jan 2026
