Scientist II, Statistical GeneticsLocation San Rafael, California Apply
Scientist 2, Statistical Genetics
BioMarin is the world leader in delivering therapeutics that provide meaningful advances to patients who live with serious and life-threatening rare genetic diseases. We target diseases that lack effective therapies and affect relatively small numbers of patients, many of whom are children. These conditions are often inherited, difficult to diagnose, progressively debilitating and have few, if any, treatment options. will continue to focus on advancing therapies that are the first or best of their kind.
Research & Development group is responsible for everything from research and discovery to post-market clinical development. Research & Development involves all bench and clinical research and the associated groups that support those endeavors. Our teams work on developing first-in-class and best-in-class therapeutics that provide meaningful advances to patients who live with rare diseases. Come join our team and make a meaningful impact on patients’ lives.
We’re seeking a statistical geneticist/genomicist to join the growing research and drug discovery group at Pharmaceutical. The Scientist II will support the discovery activities to transform human genetics and genomics discoveries to therapeutic hypotheses, and effectively communicate results to impact multiple stages of our drug discovery and development pipeline. The successful candidate will have the opportunity to work in a fast-paced and highly collaborative environment and will be responsible for developing and employing rigorous statistical and computational approaches and to engage fellow scientists and project teams to leverage genomics data in achieving project objectives.
- Apply and develop robust statistical and computational approaches to analyze SNP array, whole-exome and whole-genome sequence data in combination with phenotypic data to enable disease/target/biomarker identification and evaluation, exploring mechanism of action, and identification of genetic causal links to disease or subtypes of disease
- Work closely with project teams and functional areas to identify and provide computational solutions to address key biological questions, including identifying datasets, formulating hypothesis, developing and implementing analytical solutions
- Evaluate bioinformatics methods to integrate, summarize and report genetic, genomic, and other omics data, examples include GWAS, RVAS, Mendelian randomization, RNA-seq, scRNA-seq, WES/WGS.
- Solid foundation in population statistical genetics principles and applications
- Demonstrated knowledge and expertise with NGS and statistical genomics analyses and software
- Hands-on experience in management, analysis and interpretation of large human genomics studies (e.g. GWAS, Mendelian randomization, ENCODE)
- Statistical programming and scripting skills (R and Python/Perl/Shell/etc.)
- Demonstrated ability to work in cross-functional teams and being a highly collaborative and active team contributor
- Strong scientific curiosity and initiative, knowledge of experimental design
- Excellent problem-solving, teamwork, organization and communication skills
- Working experience with large samples combining broad phenotypic information or Electronic Health Record data with genotype/sequence data will be a plus (eg. UK Biobank, National Registries, TopMed).
- Working experience of integrating GWAS analysis with molecular profiling data will be a plus (e.g. eQTL, pQTL)
EDUCATION & Qualifications:
- Ph.D., minimum of 1-2 years post degree experience in statistical genetics, quantitative genetics, biostatistics, computational biology, or related fields