Baylor Genetics · 6 hours ago
Lead Bioinformatics Scientist
United States
Full-time
Remote
Lead/Staff
8+ years expBaylor Genetics is seeking an accomplished and visionary Lead Bioinformatics Scientist to advance innovation within the Bioinformatics R&D and Data Science organization. This individual will serve as a scientific and technical leader, driving the design, development, and implementation of advanced computational methods to enhance genomic testing and interpretation capabilities.
BiotechnologyHealth Care
Responsibilities
Serve as a scientific authority in bioinformatics, computational biology, statistical, and machine learning methods for genomic and clinical data analysis
Contribute to the strategic bioinformatics roadmap, integrating novel algorithms, predictive modeling, and AI/ML approaches to enhance diagnostic yield, turnaround time, and interpretability
Act as a subject matter expert (SME) in computational genomics, variant annotation, and clinical data integration
Translate research innovations into robust, production-ready tools and pipelines that meet clinical and regulatory requirements
Drive cross-functional collaborations to deliver scalable, interpretable, and validated computational solutions
Design, develop, and optimize bioinformatics methods and pipelines for secondary (alignment, variant calling) and tertiary (annotation, prioritization, interpretation) analysis
Implement, validate, and maintain workflows using Nextflow, Snakemake, or similar orchestration tools for reproducible, scalable analysis
Develop and evaluate computational, statistical, and machine learning models for variant classification, pathogenicity prediction, and genotype–phenotype correlation
Integrate multi-omics, phenotypic, and clinical datasets to improve analytical accuracy and discovery power
Ensure computational reproducibility, scalability, and maintainability through best practices in software engineering and CI/CD
Support clinical validation of new and developed tools and pipelines, ensuring compliance with CLIA, CAP, and related quality standards
Lead investigative projects to develop novel computational frameworks and analytical methodologies for genomic discovery and clinical interpretation
Apply and evaluate computational, statistical, ML, and AI-based methods to address key challenges in variant annotation, classification, and reporting
Design and execute benchmarking studies to evaluate new algorithms, annotation resources, and models
Contribute to the scientific community through publications, conference presentations, and collaborations
Employ advanced computational and statistical techniques to extract biological insights from genomic and clinical data
Use regression, probabilistic, and predictive models to improve variant quality metrics, scoring, and prioritization
Collaborate with data scientists and engineers to integrate ML/AI methods into clinical-grade pipelines
Utilize effective data visualization and interpretability frameworks to communicate findings to scientific and clinical audiences
Partner with clinical geneticists, molecular scientists, software engineers, and data scientists to translate R&D innovations into clinical deployment
Act as a bridge between bioinformatics R&D and clinical operations, ensuring analytical rigor and compliance with regulatory standards
Communicate technical strategies and results clearly to leadership and cross-functional stakeholders
Qualification
Required
Master's or higher degree (PhD preferred) in Bioinformatics, Computational Biology, Genomics, Computer Science, Genomic Data Science, or related quantitative field
8+ years of professional experience in bioinformatics, computational genomics, data science, or genomic R&D, including 3–5 years in a principal or leadership role
Proven expertise in pipeline development, algorithm design, and computational genomics research
Hands-on experience in secondary and tertiary genomic analysis
Demonstrated integration of statistical and data science approaches in genomics applications
Proficiency in Python, R, and at least one compiled language (C/C++, Java, or similar)
Expertise in NGS data formats and tools
Strong knowledge of clinical genomic databases and annotation resources
Solid foundation in statistical modeling, data analysis, and feature engineering for biological data
Familiarity with machine learning frameworks (TensorFlow, PyTorch, Scikit-learn, etc.) applied to genomic data
Experience with workflow orchestration tools (Nextflow, Snakemake, Cromwell) and cloud-based computing (Azure, AWS, GCP)
Experienced with data management, version control (Git), and CI/CD best practices
Knowledge of multi-omics data integration and modern visualization techniques
Strong scientific reasoning and analytical problem-solving skills
Proven ability to lead R&D initiatives from concept through validation and deployment
Deep understanding of genomic data, algorithms, and biological context
Excellent written and verbal communication for technical and clinical translation
Collaborative mindset and ability to work across disciplines
Commitment to innovation, quality, and patient-centered outcomes
Preferred
Experience working in a clinical genomics or regulated diagnostic environment strongly preferred
Company
Baylor Genetics
Baylor Genetics offers a full spectrum of cost-effective, genetic testing, and provides clinically relevant solutions.
501-1000 employees
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 StageLeadership Team
Kengo Takishima
Chairman and CEO
Recent News
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