Associate Manager, Statistical Genetics; Applied Bioinformatics Scientist

Position: Associate Manager, Statistical Genetics (Applied Bioinformatics Scientist)
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.

When & where:

Location:

Tarrytown, NYWork model/flexibility: 4 days onsite

Discover your role:
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.

This role requires:
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 Experience working with immunologic datasets and/or experience with immunology is preferred

Does this sound like you? Apply now to take your first step towards living the Regeneron Way! We are committed to building a workplace with an inclusive culture. Regeneron is an equal opportunity employer and all  qualified applicants will receive consideration for employment without regard to race, color, religion or belief (or lack thereof), sex, sexual orientation, gender identity or expression, gender reassignment, marital or civil partnership status, civil status, pregnancy or parental status, age, disability, nationality, citizenship status, ethnic or national origin, membership of the Traveler community, familial status, genetic information, military or veteran status, or any other characteristic protected under applicable law.

Where required, we will provide reasonable accommodation to applicants with known disabilities or chronic illnesses during the recruitment process, unless such accommodation would impose undue hardship.

Where…