Jobs · Analyst

Senior R&D Scientist, Algorithm Developer

Baylor Genetics · United States · Yesterday
RemoteRemoteAnalystFull-time

Key Responsibilities

  • Lead the design, optimization, and implementation of scalable NGS algorithms and pipelines for detection and interpretation of complex genomic features, including SNVs/Indels, CNVs, STRs, methylation, trisomy, PGx variants, and variants in homologous and homopolymer regions
  • Lead the design and optimization of targeted NGS panels for existing and new products
  • Drive end-to-end development, validation, benchmarking, and integration of NGS algorithms and analysis pipelines using internal and public truth sets
  • Collaborate closely with assay scientists, bioinformatics teams, software engineers, and other partners to translate biological and product requirements into computational solutions
  • Provide technical and project leadership to ensure analytical accuracy, robustness, scalability, and continuous improvement across products
  • Support technology transfer, pipeline updates, and production deployment, and contribute to scientific publications, conference presentations, and intellectual property development

Required Qualifications

  • Ph.D. in Bioinformatics, Computational Biology, Genomics, or a related discipline
  • Minimum 5 years of experience in NGS algorithm development
  • Proficiency in Python, R, C++, and workflow orchestration tools
  • Deep understanding of:
    • Read alignment and variant calling (e.g., BWA-MEM, minimap2, GATK, DeepVariant) for germline or/and somatic variants
    • CNV modeling, STR detection tools and methylation callers
    • Homologous region analysis and control gene normalization
    • PGx variant interpretation and allele resolution
  • Strong analytical, problem-solving, and communication skills

Preferred Qualifications

  • Somatic variant calling by short-reads or/and long-reads sequencing
  • Experience with machine learning models for variant classification
  • Knowledge of clinical genomics and regulatory standards
  • Familiarity with pharmacogenomic databases (e.g., PharmGKB, CPIC)

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