Senior & Staff Bioinformatics Scientist's

Overview
In this role you will help advance genomic analysis at scale by designing novel algorithms and building production-ready software for the DRAGEN platform and ICA integration. You will join a cross-functional team of scientists, engineers, and clinicians to turn complex sequencing data into actionable insights. The work spans rare disease, oncology, population genomics, and precision medicine, with a strong emphasis on impactful, real-world applications. This is a mission-driven opportunity to shape genomic technologies that improve lives through collaboration and rigorous scientific development.
Retribuzione / Benefits bonus or commission eligibility
equity potential
flexible time off
summer shutdown
pension contributions (UK)
private medical insurance (UK)
Responsabilità Design and implement computational methods for genomic data analysis
Develop high-performance production software with emphasis on speed and accuracy
Interpret complex sequencing data to support product/workflow development
Collaborate with software, FPGA, quality, clinical genomics, and product teams
Advance DRAGEN platform across germline, somatic, DNA, RNA, SV, CNV, and targeted sequencing applications
Engage with customers and researchers to understand emerging needs
Present findings to specialist and non-specialist audiences
Contribute to publications, documentation, and thought leadership
Evaluate emerging technologies to improve performance and outcomes
Foster collaboration, accountability, and innovation across teams
Requisiti fondamentali Master's or PhD in Bioinformatics, Computer Science, Statistics, Engineering, or related discipline
Strong experience developing bioinformatics methods for NGS data
Expertise in secondary analysis workflows (mapping, alignment, variant calling, genomic interpretation)
Proficiency in C/C++ or equivalent high-performance languages
Experience with large-scale genomic datasets and production software environments
Knowledge of cancer genomics, rare disease analysis, population genetics, transcriptomics, or multi-omics
curiosity
innovation
ability to collaborate across disciplines
bioinformatics methods for NGS
algorithm development
secondary analysis workflows