Manager, Statistical Genetics
Regeneron
3 hours ago
On-site
Tarrytown, NY
Clinical Research and Development
Responsibilities:
- 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.
Qualifications (You Might Be For You If You Have):
- 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 functional data to prioritize variants/genes.
- Ability to independently lead and manage research projects.
- Strong communication and collaboration skills; proven interdisciplinary teamwork.
- Ability to summarize/present results to diverse audiences.
- Strong programming skills (Python, R, C/C++, Bash, and/or Julia).
- Strong quantitative skills (regression/classification, Bayesian inference, hypothesis testing); experience with Git/GitHub, Claude, Adobe, and/or Docker.
Required:
- PhD with 3+ years of relevant experience.
- Expertise in genetic association analyses using large-scale genetic data.
- Proficiency in multi-omic data integration for therapeutic target discovery.
Preferred:
- Experience working with immunologic datasets and/or immunology.
Benefits:
- Comprehensive benefits (health and wellness programs including medical, dental, vision, life, and disability insurance; fitness centers; 401(k) match; family support benefits; equity awards; annual bonuses; paid time off; paid leaves such as military and parental leave).
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.
Qualifications (You Might Be For You If You Have):
- 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 functional data to prioritize variants/genes.
- Ability to independently lead and manage research projects.
- Strong communication and collaboration skills; proven interdisciplinary teamwork.
- Ability to summarize/present results to diverse audiences.
- Strong programming skills (Python, R, C/C++, Bash, and/or Julia).
- Strong quantitative skills (regression/classification, Bayesian inference, hypothesis testing); experience with Git/GitHub, Claude, Adobe, and/or Docker.
Required:
- PhD with 3+ years of relevant experience.
- Expertise in genetic association analyses using large-scale genetic data.
- Proficiency in multi-omic data integration for therapeutic target discovery.
Preferred:
- Experience working with immunologic datasets and/or immunology.
Benefits:
- Comprehensive benefits (health and wellness programs including medical, dental, vision, life, and disability insurance; fitness centers; 401(k) match; family support benefits; equity awards; annual bonuses; paid time off; paid leaves such as military and parental leave).
Application Instructions:
- Apply now.