Associate Manager, Statistical Genetics (Applied Bioinformatics Scientist)

Regeneron Pharmaceuticals•Tarrytown, GA

2d•$109,900 - $179,300•Hybrid

About The Position

The Regeneron Genetics Center uses genetics and health data on millions of people to advance our understanding of human disease and guide Regeneron’s therapeutic programs. This individual contributor role is responsible for conducting analyses of large-scale human genetic and phenotypic datasets for the discovery and validation of new therapeutic targets at the Regeneron Genetics Center (RGC). Work draws on both in-house and public data resources, integrating genetic data with multi-omics datasets and applying state-of-the-art statistical methodologies across analytic and translational genetics. The role collaborates closely with pre-clinical and clinical development teams colleagues across Regeneron’s R&D functions.

Requirements

PhD and 0 - 2 years of experience analyzing omics data and genetic association analyses using large-scale genetic data
Proficiency in multi-omic data integration for therapeutic target discovery
Experience developing and implementing data harmonization and normalization methods
Experience with genetic analysis approaches including GWAS, EXWAS, rare variant analysis, Mendelian randomization, LD Score regression, polygenic risk score modeling, pleiotropy analysis, meta-analysis, and use of functional data to prioritize variants and genes
Strong programming skills in languages such as Python, R, C/C++, Bash, and/or Julia.
Strong quantitative skills, including applied statistical techniques such as regression and classification, Bayesian inference, and hypothesis testing.
Experience with analytic and visualization tools including Git/Github, Claude, Adobe, Docker

Nice To Haves

Experience working with immunologic datasets and/or experience with immunology is preferred

Responsibilities

Conduct genetic association analyses using large-scale human genetic data, including genome-wide association analysis (GWAS), exome-wide association analysis (EXWAS), rare variant analysis, Mendelian randomization, LD Score regression, polygenic risk score modeling, pleiotropy analysis, and meta-analysis.
Integrate genetic data with multi-omic datasets to support therapeutic target discovery and validation.
Develop and implement methods for data harmonization and normalization across in-house and public data resources.
Apply functional genomic data to prioritize variants and genes of interest.
Perform quality control on large-scale genetic and phenotypic datasets.
Identify and interrogate data-driven hypotheses as part of analytic and translational genetics work.
Design and independently execute analytic studies from conception to completion.
Collaborate with groups across Regeneron’s R&D functions, including pre-clinical and clinical development teams, to advance therapeutic programs.