Associate Manager, Statistical Genetics
Regeneron
July 01, 2026
Remote friendly (Tarrytown, NY)
United States
Clinical Research and Development
In this role, a typical day might include:
- Conduct genetic association analyses using large-scale human genetic data, including GWAS, EXWAS, rare variant analysis, Mendelian randomization, LD Score regression, polygenic risk score modeling, pleiotropy analysis, and meta-analysis.
- Integrate genetic data with multi-omics 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 pre-clinical and clinical development teams across R&D functions to advance therapeutic programs.
This Role Might Be For You If You Have:
- Experience developing and implementing data harmonization and normalization methods.
- Experience with genetic analysis approaches (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/genes.
- Ability to independently lead and manage research projects.
- Strong communication and collaboration skills.
- Ability to summarize/present study results to diverse technical audiences.
- Strong programming skills (Python, R, C/C++, Bash, and/or Julia).
- Strong quantitative skills (regression/classification, Bayesian inference, hypothesis testing) and analytic/visualization tools (Git/GitHub, Claude, Adobe, Docker).
To Be Considered For This Role, We Require:
- PhD with 0–2 years of relevant experience.
- Expertise in genetic association analyses using large-scale genetic data.
- Proficiency in multi-omic data integration for therapeutic target discovery.
- Immunology experience preferred.
Application instructions: Apply now.
- Conduct genetic association analyses using large-scale human genetic data, including GWAS, EXWAS, rare variant analysis, Mendelian randomization, LD Score regression, polygenic risk score modeling, pleiotropy analysis, and meta-analysis.
- Integrate genetic data with multi-omics 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 pre-clinical and clinical development teams across R&D functions to advance therapeutic programs.
This Role Might Be For You If You Have:
- Experience developing and implementing data harmonization and normalization methods.
- Experience with genetic analysis approaches (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/genes.
- Ability to independently lead and manage research projects.
- Strong communication and collaboration skills.
- Ability to summarize/present study results to diverse technical audiences.
- Strong programming skills (Python, R, C/C++, Bash, and/or Julia).
- Strong quantitative skills (regression/classification, Bayesian inference, hypothesis testing) and analytic/visualization tools (Git/GitHub, Claude, Adobe, Docker).
To Be Considered For This Role, We Require:
- PhD with 0–2 years of relevant experience.
- Expertise in genetic association analyses using large-scale genetic data.
- Proficiency in multi-omic data integration for therapeutic target discovery.
- Immunology experience preferred.
Application instructions: Apply now.