Staff Bioinformatics Scientist - San Jose - AccuraGen

    AccuraGen
    AccuraGen San Jose

    1 day ago

    $1,200,000 - $1,500,000 (USD) per year
    Description

    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 Responsibilities

    • Improve and extend somatic variant-calling algorithms for tumor tissue and cfDNA-based mutation detection
    • Develop, validate, and refine MRD-calling algorithms with an emphasis on sensitivity, specificity, and robustness
    • Design and implement benchmarking, evaluation, and quality control (QC) methodologies
    • Lead troubleshooting efforts, including root-cause analysis of analytical or pipeline failures, and drive corrective actions
    • Implement algorithms in production-quality code and collaborate with engineering teams to integrate methods into scalable pipelines and workflows
    • Partner with assay development teams on new technologies and assay iterations requiring customized analysis strategies and algorithm development
    • Document analytical methods, validation results, and design decisions; clearly communicate findings, limitations, and trade-offs to technical and cross-functional stakeholders

    Requirements

    • Ph.D. in Statistics, Biostatistics, Computer Science, Bioinformatics, Computational Biology, Applied Mathematics, or a related field, with relevant postdoctoral or industry experience
    • Strong foundation in statistical inference and modeling, including uncertainty quantification and decision thresholding
    • Prior experience working with genomics data, including WGS or large-scale NGS datasets, and a solid understanding of technical and biological noise sources
    • Demonstrated software implementation skills in Python and/or a performance-oriented language (e.g., C++, Rust, Java), with experience writing maintainable, testable, production-quality code
    • Familiarity with standard genomics data formats and tooling (e.g., FASTQ, BAM/CRAM, VCF) and common processing workflows
    • Experience working in regulated product development environments (e.g., FDA, IVD), including documentation practices, analytical validation, and design controls
    • Excellent communication and collaboration skills, with the ability to work effectively across research, engineering, and assay development teams

    Preferred Qualifications

    • Hands-on experience with cfDNA analysis and/or MRD detection, including ultra-low-frequency variant calling and/or epigenetics-based analyses
    • Machine learning experience, particularly in settings involving class imbalance, model evaluation, calibration, and decision optimization
    • Experience collaborating closely with assay development teams on experimental design, data analysis planning, and iterative assay optimization

    Benefits

    • Health Care Plan (Medical, Dental & Vision)
    • Retirement Plan (401k, IRA)
    • Paid Time Off (Vacation, Sick & Public Holidays)
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