Position SummaryThis 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.
Key Responsibilities - 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 - 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
