Lead Bioinformatics Scientist

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Baylor Genetics

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 1978

🏥 Healthcare

💼 Consulting

🍽️ Food & Beverage

Healthcare • Consulting • Food & Beverage

Baylor Genetics is a clinical genomics and precision diagnostics laboratory affiliated with Baylor College of Medicine that provides comprehensive genetic testing and interpretation services. The company offers whole genome and whole exome sequencing, chromosomal microarray analysis, mitochondrial testing, pharmacogenomics, and specialized assays, along with genetic counseling, provider support, and insurance/payment resources. Baylor Genetics supports healthcare providers, researchers, and families with AI-enhanced interpretation, multimodal data integration, and end-to-end clinical and laboratory services.

📋 Description

• 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.

🎯 Requirements

• 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. • Experience working in a clinical genomics or regulated diagnostic environment strongly preferred. • 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.

🏖️ Benefits

• EEO Statement: Baylor Genetics is proud to be an equal opportunity employer dedicated to building an inclusive and diverse workforce. We do not discriminate based on race, religion, color, national origin, sex, sexual orientation, age, gender identity, veteran status, disability, genetic information, pregnancy, childbirth, or related medical conditions, or any other status protected under applicable federal, state, or local law.