Jobs at Baylor Genetics

This position requires thorough documentation of analytical methods, validation studies, and pipeline updates in technical reports, supporting both internal development and regulatory needs. The R&D Scientist will work collaboratively with cross functional teams, including assay development, bioinformatics, and quality groups.

Candidates should hold a Ph.D. in Bioinformatics, Computational Biology, Genomics, Computer Science, or a related field, or an M.S. with 3+ years of relevant experience. Required expertise includes hands on-experience with NGS data analysis, particularly sequencing performance metrics, as well as strong programming skills in Python and/or R.

• Perform in-depth analytical analysis of NGS sequencing data to evaluate sequencing performance metrics and support assay development
• Validate and verify computational algorithms used within NGS analysis pipelines
• Support NGS panel design activities, including analytical assessment and quality considerations
• Conduct end-to-end validation of NGS analysis pipelines to ensure accuracy, reproducibility, and robustness
• Support quality assurance efforts through data review, troubleshooting, and performance monitoring
• Document analytical methods, validation studies, and pipeline updates in clear, well-structured technical reports
• Collaborate with cross functional teams, including assay development, bioinformatics, and quality, to support R&D objective

Required Qualifications

• Ph.D. in Bioinformatics, Computational Biology, Genomics, Computer Science, or a related field; or M.S. with 3+ years of relevant experience
• Hands-on experience with NGS data analysis, including evaluation of sequencing performance metrics and assay quality
• Experience validating computational algorithms or bioinformatics analysis pipelines
• Proficiency in Python and/or R for data analysis and pipeline development
• Strong analytical, documentation, and collaboration skills within a cross functional R&D environment

Preferred Qualifications

• Preferred experience with Linux/HPC, Docker containerization, Nextflow workflow development, GitHub-based software engineering, and Python/Groovy programming. Familiarity with cloud platforms and NGS data formats (FASTQ, BAM, VCF), along with CI/CD, workflow automation, troubleshooting, and developing reproducible bioinformatics pipelines.
• Knowledge of clinical genomics applications, including NIPT or cancer genomics
• Experience or familiarity with pharmacogenomics (PGx) and complex variant analysis
• Exposure to rare disease genomics and germline variant analysis