What are the responsibilities and job description for the Senior Staff Bioinformatics Scientist position at AccuraGen?
As a Senior Staff Bioinformatics Scientist at AccuScan Science, you will lead the development and improvement of statistical and algorithmic methods for NGS-based variant detection and minimal residual disease (MRD) calling. This role focuses on tumor/normal variant calling in tissue samples as well as ultra–low-frequency mutation detection in cfDNA.You will work closely with assay development, bioinformatics engineering, and R&D teams to translate new technologies into robust, production-ready analytical pipelines. The ideal candidate brings deep statistical modeling expertise, strong hands-on implementation skills, and experience working with WGS or large-scale sequencing data. Prior exposure to regulated (FDA/IVD) environments and machine learning is a strong plus.Key ResponsibilitiesImprove and extend somatic variant-calling algorithms for tumor tissue and cfDNA-based mutation detectionDevelop, validate, and refine MRD-calling algorithms with an emphasis on sensitivity, specificity, and robustnessDesign and implement benchmarking, evaluation, and quality control (QC) methodologiesLead troubleshooting efforts, including root-cause analysis of analytical or pipeline failures, and drive corrective actionsImplement algorithms in production-quality code and collaborate with engineering teams to integrate methods into scalable pipelines and workflowsPartner with assay development teams on new technologies and assay iterations requiring customized analysis strategies and algorithm developmentDocument analytical methods, validation results, and design decisions; clearly communicate findings, limitations, and trade-offs to technical and cross-functional stakeholdersRequirementsPh.D. in Statistics, Biostatistics, Computer Science, Bioinformatics, Computational Biology, Applied Mathematics, or a related field, with relevant postdoctoral or industry experienceStrong foundation in statistical inference and modeling, including uncertainty quantification and decision thresholdingPrior experience working with genomics data, including WGS or large-scale NGS datasets, and a solid understanding of technical and biological noise sourcesDemonstrated software implementation skills in Python and/or a performance-oriented language (e.g., C , Rust, Java), with experience writing maintainable, testable, production-quality codeFamiliarity with standard genomics data formats and tooling (e.g., FASTQ, BAM/CRAM, VCF) and common processing workflowsExperience working in regulated product development environments (e.g., FDA, IVD), including documentation practices, analytical validation, and design controlsExcellent communication and collaboration skills, with the ability to work effectively across research, engineering, and assay development teamsPreferred QualificationsHands-on experience with cfDNA analysis and/or MRD detection, including ultra–low-frequency variant calling and/or epigenetics-based analysesMachine learning experience, particularly in settings involving class imbalance, model evaluation, calibration, and decision optimizationExperience collaborating closely with assay development teams on experimental design, data analysis planning, and iterative assay optimizationBenefitsHealth Care Plan (Medical, Dental & Vision)Retirement Plan (401k, IRA)Paid Time Off (Vacation, Sick & Public Holidays)