SUMMARY
We are seeking a highly experienced and innovative Senior Scientist in NGS Algorithm Development to lead the design, optimization, and implementation of computational algorithms for next-generation sequencing (NGS) data. This role focuses on detecting and interpreting a wide range of genomic features and chromosomal abnormalities, including trisomy, small variants, copy number variants, short tandem repeats, methylation patterns, and variants in homologous and homopolymer regions.
The Senior Scientist will also lead the design and optimization of targeted NGS panels for existing and new products and drive the development, validation, and integration of NGS algorithms and analysis pipelines. As a technical and project lead, this role ensures analytical accuracy, robustness, and scalability across products, supports technology transfer and pipeline updates, and collaborates cross-functionally with assay development, bioinformatics, and partner teams to provide technical guidance and inform strategic decisions.
The ideal candidate will hold a Ph.D. in Bioinformatics, Computational Biology, Genomics, or a related field, and have at least 5 years of hands-on experience in algorithm development for NGS applications. Experience in pharmacogenomics (PGx) variant calling, including complex loci such as CYP2D6, is strongly preferred.
Key Responsibilities
- Lead the design, optimization, and implementation of scalable NGS algorithms and pipelines for detection and interpretation of complex genomic features, including SNVs/Indels, CNVs, STRs, methylation, trisomy, PGx variants, and variants in homologous and homopolymer regions
- Lead the design and optimization of targeted NGS panels for existing and new products
- Drive end-to-end development, validation, benchmarking, and integration of NGS algorithms and analysis pipelines using internal and public truth sets
- Collaborate closely with assay scientists, bioinformatics teams, software engineers, and other partners to translate biological and product requirements into computational solutions
- Provide technical and project leadership to ensure analytical accuracy, robustness, scalability, and continuous improvement across products
- Support technology transfer, pipeline updates, and production deployment, and contribute to scientific publications, conference presentations, and intellectual property development.
Required Qualifications
- Ph.D. in Bioinformatics, Computational Biology, Genomics, or a related discipline
- Minimum 5 years of experience in NGS algorithm development
- Proficiency in Python, R, C++, and workflow orchestration tools
- Deep understanding of:
- Read alignment and variant calling (e.g., BWA-MEM, minimap2, GATK, DeepVariant) for germline or/and somatic variants
- CNV modeling, STR detection tools and methylation callers
- Homologous region analysis and control gene normalization
- PGx variant interpretation and allele resolution
- Experience with long-read technologies (ONT, PacBio) and signal-level data
- Strong analytical, problem-solving, and communication skills
Preferred Qualifications
- Somatic variant calling by short-reads or/and long-reads sequencing
- Experience with machine learning models for variant classification
- Knowledge of clinical genomics and regulatory standards
- Familiarity with pharmacogenomic databases (e.g., PharmGKB, CPIC)
PHYSICAL DEMANDS AND WORK ENVIRONMENT
- Frequently required to sit or stand for extended periods.
- Frequently required to use hand and finger dexterity to operate laboratory equipment.
- Frequently required to communicate verbally and visually interpret technical data.
- Occasionally exposed to bloodborne or airborne pathogens or infectious materials.
- Work is primarily performed in a laboratory and office environment.
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.
Note to Recruiters:
We value building direct relationships with our candidates and prefer to manage our hiring process internally. While we occasionally partner with select recruitment agencies for specialized roles, we do not accept unsolicited resumes from recruiters or agencies without a written agreement executed by the authorized signatory for Baylor Genetics ("Agreement"). Any resumes submitted to Baylor Genetics in the absence of an Agreement executed by Baylor Genetics' authorized signatory, will be considered the property of Baylor Genetics, and Baylor Genetics will not be obligated to pay any associated recruitment fees.
