Baylor Genetics · 2 hours ago
Principal Bioinformatics Scientist
Baylor Genetics is seeking an accomplished Principal Bioinformatics Scientist to join the Bioinformatics R&D and Data Science organization. This individual will serve as a senior technical expert responsible for developing, optimizing, and maintaining the computational methods and pipelines that power Baylor Genetics’ genomic testing and interpretation platforms.
BiotechnologyHealth Care
Responsibilities
Design, develop, and optimize computational workflows and pipelines for secondar and tertiary genomic analyses
Implement reproducible and scalable bioinformatics workflows using Nextflow, Snakemake, or similar orchestration frameworks
Develop, evaluate, and apply algorithms and statistical or machine learning models for variant detection, classification, and genotype–phenotype correlation
Integrate multi-omics, phenotypic, and clinical datasets to enhance analytical accuracy and interpretability
Translate R&D innovations into production-ready tools that improve diagnostic accuracy, speed, and reproducibility
Provide ongoing support and maintenance for bioinformatics systems and pipelines, ensuring operational stability, accuracy, and efficiency
Actively collaborate with clinical and laboratory teams to investigate and resolve pipeline bugs, data inconsistencies, and performance issues
Participate in root-cause analyses and implement sustainable solutions to ensure reliable clinical operations
Work closely with clinical stakeholders to define, design, and deploy enhancements and new system capabilities based on user feedback and evolving clinical requirements
Ensure all production updates and improvements comply with regulatory and quality standards (CLIA, CAP, etc.) and are appropriately documented and validated
Support the design and validation of new computational tools and pipelines according to clinical genomic standards and regulatory requirements
Conduct analytical validation, benchmarking, and verification of newly developed algorithms and workflows
Collaborate with quality, laboratory, and clinical teams to ensure smooth transition of tools from R&D to production
Lead exploratory projects to develop and assess novel computational or statistical methods for variant classification, annotation, and interpretation
Perform benchmarking studies to evaluate emerging algorithms, annotation resources, and data integration approaches
Contribute to internal documentation, publications, and presentations highlighting R&D advancements
Collaborate closely with data scientists, software engineers, and clinical scientists on cross-functional R&D and production initiatives
Provide technical mentorship and peer review for bioinformatics scientists and analysts
Promote best practices in scientific computing, code reproducibility, and analytical rigor
Maintain clear, version-controlled documentation of all analytical pipelines and validation processes
Contribute to continuous improvement of computational infrastructure, software practices, and data management
Stay current with evolving trends, standards, and technologies in computational genomics and clinical bioinformatics
Qualification
Required
Master's or higher degree (PhD preferred) in Bioinformatics, Computational Biology, Genomics, Computer Science, or a related quantitative field
6+ years of professional experience in bioinformatics, computational genomics, or computational biology, including extensive hands-on work with large-scale NGS datasets
Proven experience developing and maintaining bioinformatics pipelines in both R&D and production settings
Strong record of integrating computational, statistical, and/or machine learning methods into genomics applications
Demonstrated success collaborating with clinical or laboratory teams to troubleshoot and improve production systems
Proficiency in Python and R; familiarity with one or more compiled languages (C/C++, Java, or similar)
Strong experience with NGS data formats and tools
Expertise with workflow orchestration frameworks (Nextflow, Snakemake, Cromwell)
Deep knowledge of genomic databases
Familiarity with cloud computing (Azure, AWS, GCP), containerization (Docker/Kubernetes), and version control (Git)
Core Competencies: Strong scientific reasoning and analytical problem-solving abilities
Hands-on approach to both R&D innovation and operational troubleshooting
Ability to collaborate effectively with multidisciplinary teams
Excellent written and verbal communication skills
Commitment to quality, compliance, and scientific excellence in a clinical setting
Preferred
Experience working in a clinical genomics or regulated diagnostic environment strongly preferred
Background in statistical modeling, data analysis, and machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch) preferred
Knowledge of multi-omics data integration and data visualization methods a plus
Company
Baylor Genetics
Baylor Genetics offers a full spectrum of cost-effective, genetic testing, and provides clinically relevant solutions.
H1B Sponsorship
Baylor Genetics has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (3)
2024 (1)
2023 (3)
2022 (1)
2021 (1)
2020 (3)
Funding
Current Stage
Late StageRecent News
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