Manager, Translational Genetics (Therapeutic Area Genetics)
Regeneron
Full-time
Remote friendly (Tarrytown, NY)
United States
IT
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Role Summary
Manager, Translational Genetics (Therapeutic Area Genetics) responsible for developing and maintaining applications and libraries to analyze and interpret large-scale human genetic data, enabling scientists to interact with analysis results from massive sequencing projects. Focus on delivering high-quality, flexible tools for large-scale genomic analysis and interpretation. Requires proven experience in bioinformatics software, libraries, or applications.
Responsibilities
- Design and implement R libraries and web applications to fit translational research needs.
- Modernize and optimize existing code bases to improve performance, scalability, portability, and testability.
- Collaborate with other developers on high-priority tasks.
- Provide user support by answering questions, understanding use cases, fixing bugs, and writing documentation.
- Communicate with and brainstorm analysis strategies with colleagues from diverse backgrounds (scientists, clinicians, analysts, bioinformaticians).
- Mine large sequencing datasets to generate biological hypotheses and integrate data sources to derive new inferences.
Qualifications
- Master's degree in Computer Science, Bioinformatics, Biomedical Engineering, or related field with 6+ years of relevant experience; Doctoral degree encouraged.
- Strong expertise in writing efficient R code using standard libraries; R package development or multi-user R Shiny applications a plus.
- Experience deploying in cloud infrastructure (AWS, GCP, DNAnexus) with CI/CD and containerization (Docker).
- Familiarity with bioinformatics tools (PLINK2, HTSlib, tabix) and data formats (VCF, BED, BGEN).
- Experience with Linux/UNIX command line and SQL databases.
Skills
- Robust tool development and problem-solving for creative data analysis.
- Experience implementing scalable software tools, applications, and workflows in cloud environments.
- User-facing development with ability to gather requirements and translate them into solutions.
- Knowledge of statistical genetics, human genetics, software development, or computational genomics.
- Effective communication of methods and code to diverse audiences.
Education
- Master's degree in Computer Science, Bioinformatics, Biomedical Engineering, or related field (Doctoral degree encouraged).