Sr Bioinformatics Scientist – Algorithm & Assay Development (Remote, US)
About The Position
The Senior Bioinformatics Scientist will develop, optimize, and validate clinical-grade next-generation sequencing (NGS) algorithms supporting oncology diagnostics, liquid biopsy, and solid tumor genomic assays. The role focuses on cancer genomics, ctDNA analysis, variant calling, algorithm development, statistical modeling, and analytical validation in regulated clinical environments. The position collaborates with software engineering, assay development, clinical, and regulatory teams to deliver and integrate algorithms into production pipelines. It also involves leading proof-of-concept studies, preparing validation reports, supporting regulatory documentation, and troubleshooting clinical NGS analysis pipelines. The role is remote in the United States and is offered as a contract engagement lasting at least six months, with a high possibility of extension.
Requirements
- PhD in Bioinformatics, Computational Biology, Applied Statistics, or a related field with at least 4 years of relevant experience; alternatively, a Master's or Bachelor's degree with additional industry experience.
- Strong experience in NGS data analysis, cancer genomics, and clinical oncology diagnostics.
- Hands-on experience developing and validating NGS variant-calling algorithms.
- Expertise in SNVs, indels, CNVs, structural variants, and somatic variant detection.
- Experience with ctDNA, liquid biopsy, or oncology assay development.
- Strong proficiency in Python and/or R.
- Experience with GATK, Mutect2, VarDict, VEP, SnpEff, BWA, Samtools, BEDTools, VCF, and BAM.
- Experience conducting analytical validation studies and evaluating assay performance.
- Knowledge of CLIA, CAP, FDA, and clinical diagnostic regulatory requirements.
- Strong analytical, problem-solving, and communication skills.
Nice To Haves
- Experience with DRAGEN, Sentieon, Nextflow, Seqera, or AWS HealthOmics.
- Familiarity with cancer genomics databases such as TCGA, COSMIC, gnomAD, and dbSNP.
- Experience with machine learning, statistical classifiers, and biomarker discovery.
- Knowledge of ISO 13485, IEC 62304, or ISO 15189.
Responsibilities
- Develop and optimize NGS algorithms to detect SNVs, indels, CNVs, structural variants, and RNA biomarkers.
- Design algorithms and analytical methodologies for ctDNA, liquid biopsy, and oncology diagnostics.
- Apply statistical modeling and machine learning techniques to improve assay performance.
- Design and execute analytical validation studies, including assessments of sensitivity, specificity, and limit of detection (LoD).
- Develop and monitor clinical-grade quality control (QC) metrics.
- Analyze cancer genomics data using Python, R, and established bioinformatics tools.
- Collaborate with software engineering teams to integrate algorithms into scalable production pipelines using Nextflow, Seqera, and AWS HealthOmics.
- Prepare validation reports and support regulatory documentation for CLIA, CAP, and FDA requirements.
- Lead proof-of-concept studies and collaborate with assay development, clinical, and regulatory teams.
- Troubleshoot and optimize clinical NGS analysis pipelines.
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What This Job Offers
Career Level
Senior
Education Level
Ph.D. or professional degree
