Bioinformatics / Computational Biologist

Job Summary

We are seeking a Bioinformatics/Computational Biologist to analyze complex biological datasets, develop and apply computational methods, and support research and development efforts through data-driven insights. This role bridges biology, statistics, and computer science, working closely with wet-lab scientists, data scientists, and R&D teams to translate large-scale biological data into actionable findings.

Key Responsibilities

• Design, develop, and apply bioinformatics pipelines and computational tools to analyze genomic, transcriptomic, proteomic, and/or other omics data
• Perform statistical analysis and data mining on large-scale biological datasets (NGS, microarray, sequencing data, etc.)
• Develop and maintain software, scripts, and workflows for data processing, quality control, and analysis
• Collaborate with laboratory scientists to design experiments and interpret computational results in a biological context
• Build and maintain databases and data management systems for biological research data
• Apply machine learning, statistical modeling, and/or algorithm development to biological research questions
• Visualize and communicate complex analytical results to both technical and non-technical stakeholders
• Stay current with emerging tools, methods, and literature in bioinformatics and computational biology
• Document methods, workflows, and results in accordance with research and regulatory standards
• Contribute to publications, patents, and internal reports as needed

Required Qualifications

• Master's or Ph.D. in Bioinformatics, Computational Biology, Genomics, Computer Science, Statistics, or a related field (or equivalent experience)
• Proficiency in programming languages such as Python, R, or similar
• Experience with bioinformatics tools and pipelines (e.g., BLAST, GATK, Bioconductor, Nextflow, Snakemake)
• Strong understanding of molecular biology and genetics fundamentals
• Experience working with next-generation sequencing (NGS) data and associated analysis workflows
• Familiarity with Linux/Unix environments and high-performance/cloud computing (AWS, GCP, or similar)
• Strong statistical analysis skills
• Excellent written and verbal communication skills

Preferred Qualifications

• Experience with machine learning/deep learning applied to biological data
• Familiarity with SQL and database management
• Experience with version control (Git) and reproducible research practices
• Knowledge of regulatory or GxP environments (pharma/biotech/animal health settings)
• Prior experience in a relevant industry (pharmaceutical, animal health, agbio, biotech)
• Publication record in relevant scientific journals

Core Competencies

• Analytical and problem-solving mindset
• Ability to work cross-functionally with lab scientists, data engineers, and leadership
• Attention to detail and rigorous, reproducible methodology
• Comfort working independently in a fast-paced, evolving research environment