Senior Manager, Analytical Genetics and Data Science

We are seeking a highly motivated and talented Senior Manager, Analytical Genetics and Data Science to join the AGDS team at the Regeneron Genetics Center (RGC) to drive innovation in large-scale proteomic analyses. In this role, you will design and lead proteomic-based predictive models at scale, with an emphasis on age-related diseases and healthy aging. Additional focus areas include the integration of multi-omic datasets, methods development for improved data harmonization and portability, and therapeutic target identification in collaboration with other RGC teams.

Key Responsibilities

• Plan, develop, and execute large-scale analyses of proteomic datasets, with an emphasis on aging and age-related diseases
• Implement and refine machine learning techniques to build predictive models and generate insights from multi-omic datasets
• Establish methods for data harmonization and normalization across distinct cohorts to ensure consistency and reproducibility of results
• Drive integration of proteomic, genomic, and other multi-omic data to improve therapeutic target discovery and prioritization
• Lead the creation of reproducible workflows and pipelines for multi-omic data analysis
• Collaborate with cross-functional teams to drive large-scale omics projects and shape translational research goals
• Stay abreast of emerging trends in proteomics, machine learning, and multi-omics to continuously enhance analytical strategies

Preferred Qualifications

• Proficiency in Python and R, with experience in workflow languages such as WDL
• Demonstrated expertise in machine learning and predictive analytics applied to biological data
• Deep expertise in multi-omic data integration and its application in therapeutic target discovery
• Experience in developing and implementing methods for data harmonization and normalization
• Proven ability to design and lead complex research programs from conception to completion
• Excellent communication and collaboration skills, with a track record of working effectively in interdisciplinary teams

Requirements

• PhD, MD, or MD/PhD in a relevant field (e.g., bioinformatics, computational biology, genetics, or related disciplines)
• At least 5 years of post-PhD experience in analyzing large-scale omics datasets, with a focus on proteomics