[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 and data visualization methods a plus. Company Overview • Baylor Genetics offers a full spectrum of cost-effective, genetic testing, and provides clinically relevant solutions. It was founded in 1978, and is headquartered in Houston, Texas, USA, with a workforce of 501-1000 employees. Its website is https://www.baylorgenetics.com/. Company H1B Sponsorship • Baylor Genetics has a track record of offering H1B sponsorships, with 3 in 2025, 1 in 2024, 3 in 2023, 1 in 2022, 1 in 2021, 3 in 2020. Please note that this does not guarantee sponsorship for this specific role. Apply tot his job Apply To this Job