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

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

Timing