Senior Manager Statistical Genetics

Role Summary

We are seeking a highly motivated Senior Manager, Analytical Genetics and Data Science (AGDS) to join the AGDS team at the Regeneron Genetics Center (RGC). In this individual contributor role, you will conduct analyses of large-scale human genetic and phenotypic datasets for the discovery and validation of new therapeutic targets. Your work will use both in-house and public data resources, and your responsibilities will include integrating genetic data with other multi-omics data, applying state of the art statistical tools and methodologies, performing QC, and identifying and interrogating data driven hypotheses related to analytic and translational genetics. In addition to designing and executing analytic studies, you will collaborate with groups across Regeneron’s R&D functions, including both pre-clinical and clinical development teams.

Responsibilities

• Demonstrated expertise in genetic association analyses using large-scale genetic data.
• Strong understanding of multi-omic data integration and its application in therapeutic target discovery.
• Experience in developing and implementing methods for data harmonization and normalization.
• Experience with cutting edge genetic analysis approaches, such as genome-wide association analysis, exome-wide association analysis, rare variant analysis, Mendelian randomization, LD Score regression, polygenic risk score modelling, pleiotropy analysis, meta-analysis, and the use of functional data to prioritize variants and genes of interest.
• Proven ability to independently lead and manage research projects from conception to completion.
• Excellent communication and collaboration skills, with a track record of working effectively in interdisciplinary teams.

Qualifications

• Required: A PhD in a relevant field (e.g., statistical genetics, bioinformatics, computational biology, genetics, or related disciplines).
• Required: 5 years of post-PhD experience in analyzing large-scale omics datasets.
• Required: Outstanding communication skills and an ability to summarize and present the results of human genetic studies to a variety of technical audiences, ranging from specialists in statistical genetics and computation to specialists in biology, drug design, and medicine.

Skills

• Genetic association analyses using large-scale genetic data.
• Multi-omic data integration for therapeutic target discovery.
• Data harmonization and normalization methods.
• Genome-wide association analysis (GWAS), exome-wide association analysis, rare variant analysis, Mendelian randomization, LD Score regression, polygenic risk score modelling, pleiotropy analysis, meta-analysis, and functional data to prioritize variants and genes of interest.
• Project leadership and independent research project management.
• Excellent communication and collaboration in interdisciplinary teams.

Education

• PhD in statistical genetics, bioinformatics, computational biology, genetics, or related disciplines.