Associate Manager, Statistical Genetics
: Job Details :

Statistical Geneticist

We are looking for a statistical geneticist to contribute to the analysis and interpretation of millions of genotyped and sequenced humans linked with rich phenotype data from around the world. You will leverage these data to gain new insights into disease mechanisms and generate new discoveries that enable Regeneron to create and deliver better medicines to patients in need. Within the broad domain of cardiovascular, metabolic disease, and skeletal diseases, you will work collaboratively with other specialists in genomic data analysis, translational genetics, functional biology, and medicine, to design, execute, and refine analyses that connect genetic variation to human health and disease. You will help develop and implement statistical and computational tools that will allow these analyses to be executed and interpreted at scale.

A typical day might include the following:

• Perform genome scale analyses with genotype, imputed, and sequence data from millions of individuals across hundreds of relevant phenotypes and biomarkers.
• Work across teams to maintain and improve analytical workflows and implement analytical best practices.
• Integrate computational tools and diverse molecular data types to generate insights about human disease, interpret results, and prioritize candidate therapeutic targets.
• Critically review and provide input on analysis plans, results, and summaries to ensure accuracy and reliability. Identify problems and propose solutions or analytical refinements.

This role might be for you if you:

• Have experience in the analysis of large genetic association studies and meta-analysis, including through the analysis of UK Biobank or other biobank-scale data.
• Have experience in the management of genetic and phenotype data in human genetic studies, including familiarity manipulating sequence data (e.g., VCF files), strategies for genotype imputation, and for quality control of genetic association inputs and outputs.
• Have demonstrated coding ability in either Python, C/C++, or R.
• Enjoy working in a highly interactive environment with a diverse team of colleagues.
• Employ outstanding communication skills to summarize and present new concepts, methods, and results from human genetic studies to a variety of audiences.

To be considered for this role, you must have a PhD in Human Genetics, Biostatistics, or a related field with a minimum of 0-2 years of experience, postdoctoral training or relevant industry experience is preferred. The successful candidate should have experience and competence with approaches currently employed in the group, including genome- and exome-wide association analysis, rare variant analysis, Mendelian randomization, LD Score regression, polygenic risk score modelling, meta-analysis, and the use of functional data to prioritize variants and genes of interest. Expertise with cloud computing environments, advanced tools for genomic analyses (PLINK, REGENIE, etc.), and statistical analysis and computation (R, Python, C/C++) are necessary. Experience working in cardiovascular, metabolic, and/or musculoskeletal disease is preferred.