Job description

Position Summary 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. 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 • 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

Requirements

Must-haves

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
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

Nice-to-haves

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

Application prep

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Keywords to mirror

pythondockerci/cd

Platform: ukg
Effort: medium