Senior Staff Bioinformatics Scientist — DNA/RNA Secondary Analysis Algorithms Full-time

Sr. Staff Bioinformatics Scientist

What if the work you did every day could impact the lives of people you know? Or all of humanity? At Illumina, we are expanding access to genomic technology to realize health equity for billions of people around the world. Our efforts enable life-changing discoveries that are transforming human health through the early detection and diagnosis of diseases and new treatment options for patients. Working at Illumina means being part of something bigger than yourself. Every person, in every role, has the opportunity to make a difference. Surrounded by extraordinary people, inspiring leaders, and world changing projects, you will do more and become more than you ever thought possible.

The DRAGEN Bioinformatics team develops industry-leading secondary analysis solutions for DNA and RNA NGS applications used by researchers and clinicians worldwide. Our team builds high-performance, scalable algorithms and software for transcriptomics, oncology, population genomics, and multiomic analysis. We leverage advanced computational methods, machine learning, artificial intelligence, foundation models, and cloud technologies to transform genomic data into actionable insights.

We are seeking a Sr. Staff Bioinformatics Scientist with deep expertise in transcriptomics, computational biology, and bioinformatics software development to help advance the next generation of DRAGEN analysis solutions. The successful candidate will combine biological insight with strong algorithmic, statistical, and software engineering skills, and will provide technical leadership and product development experience across multiple product cycles.

Responsibilities

• Lead development of novel algorithms and analytical methods for RNA and multiomic sequencing applications.
• Design, evaluate, and implement scalable bioinformatics algorithms and methods for bulk RNA-seq, single-cell sequencing, CRISPR/Perturb-seq analysis, ATAC-seq, CROP-seq, and emerging multiomic assays.
• Apply machine learning, AI-based methods, foundation models, LLM-enabled workflows, and biological foundation models to accelerate method development, validation, interpretation, and product innovation.
• Develop production-quality software solutions in collaboration with bioinformatics scientists, software engineers, FPGA engineers, assay development teams, and product teams.
• Lead technical projects, define requirements, influence product direction, evaluate risks, and drive innovation across multiple product cycles.
• Mentor scientists and engineers and contribute to scientific and technical leadership within the organization.
• Evaluate emerging technologies and identify opportunities for new features, products, analytical capabilities, and intellectual property.

Required Qualifications

• PhD in Bioinformatics, Computational Biology, Computer Science, Statistics, Biology, or a related discipline, or equivalent industry experience.
• Significant experience developing DNA/RNA bioinformatics algorithms, analytical methods, and production software for NGS applications, such as genome alignment. Transcript expression, calling fusions and splice variants in RNA, and calling small and large (structural, CNV) in DNA
• Strong background in genomics, transcriptomics and biological data analysis.
• Proficiency in one or more programming languages such as C++, Python, or similar.
• Experience designing, validating, benchmarking, and interpreting computational methods for complex biological datasets.
• Demonstrated technical leadership and ability to independently drive complex projects from concept to product delivery.
• Strong communication and collaboration skills with the ability to influence cross-functional teams and technical strategy.
• Track record of innovation through publications, patents, invention disclosures, open-source contributions, or commercial product development.

Preferred Qualifications

• Experience with bulk RNA-seq, gene expression analysis, alternative splicing, gene fusion detection, and RNA biomarker development.
• Experience applying machine learning, artificial intelligence, or modern data science techniques to biological data analysis, method development, or software validation.
• Experience with single-cell genomics and transcriptomics workflows.
• Experience with CRISPR/Perturb-seq analysis, CROP-seq, ATAC-seq, spatial transcriptomics, CROP-seq, or other multiomic assays.
• Experience using AI-assisted software development and scientific analysis tools to accelerate method development, testing, validation, or interpretation.
• Experience with cloud computing, distributed computing, or large-scale genomic data processing.
• Knowledge of oncology, clinical genomics, population genomics, translational research, or biotechnology product development.
• Experience/Education:
• Typically requires a minimum of 12 years of related experience with a Bachelor's degree; or 8 years and a Master's degree; or a PhD with 5 years of experience; or equivalent experience.