[Remote] Principal Bioinformatics Scientist

Note: The job is a remote job and is open to candidates in USA. 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 and maintaining the computational methods and pipelines that power genomic testing and interpretation platforms.

Responsibilities

• Design, develop, and optimize computational workflows and pipelines for secondary 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.

Skills

• Master’s or higher degree 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).
• 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.
• PhD in Bioinformatics, Computational Biology, Genomics, Computer Science, or a related quantitative field.
• 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

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