We are looking for a statistical geneticist to excited to build tools, workflows, and applications to analyze and interpret the genetics of nearly 3 million individuals linked with rich phenotype data from around the world. You will build and maintain a suite of tools to manage, execute, and assess genome-wide analyses leading to new discoveries and insights into disease mechanisms. Within the broad domain of cardiovascular, metabolic, and skeletal diseases, you will work collaboratively with other specialists in genomic data analysis, translational genetics, functional biology, and medicine, to enable Regeneron to create better medicines for patients in need.
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 build, maintain, and improve analytical workflows that implement analytical best practices.
Build and manage systems to execute genomic analysis on a large scale and at high throughput. This including tools for analysis tracking and post-analysis quality control.
Employ your expertise in genetic analysis to identify and troubleshoot analyses at scale.
Test and integrate computational tools for deployment across our collection of diverse quantitative, health outcomes, and molecular data types.
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.
Are experienced, interested, and excited to be part of a team identifying the next generation of therapeutic targets for cardiovascular, metabolic, and skeletal diseases.
To be considered for this role, you must have a PhD in Human Genetics, Biostatistics, or a related field. No post-graduate experience is required, but 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 diseases is preferred.
Salary Range (annually)
$109,900.00 - $179,300.00
