Sr. Staff Scientist\Associate Director Statistical Genetics

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Job Description

Company Description:
The Regeneron Genetics Center is a wholly-owned subsidiary of the Company organized to collaborate with health systems and research groups to elucidate, on a large scale, genetic factors that cause or influence a range of human diseases. Building upon Regeneron's strengths in mouse genetics and genetics-driven drug discovery and development, the Center will specialize in ultra-high-throughput exome sequencing and computational biology; discovery of genotype-phenotype associations through linkage to well-annotated de-identified patient electronic medical records; and validation of discoveries using Regeneron’s VelociGene® technology. Our interests encompass a breadth of different areas such as Mendelian and family frameworks, large-scale population genetics (both common and rare variants), and gene-gene interactions. Program goals include target discovery, indication discovery, and patient-disease stratification. Objectives include advancing basic science around the world through public sharing of discoveries, providing clinically-valuable insights to physicians and patients of collaborating health-care systems, and identifying novel targets for drug development.

The Sr. Staff Scientist/Associate Director, Statistical Genetics will be responsible for contributing to the design and interpretation of all studies within the department and in collaboration with other departments such research or clinical development and regulatory affairs. Primary responsibilities will include (i) working closely with the computational biologists and programmers to support development of algorithms and automated pipelines for analysis of NGS data, (ii) working with database administrators to optimize data structures and management for downstream retrieval, access, and analysis, and (iii) to lead experimental design and association analyses. The ideal candidates will have strong statistical and programming proficiencies with proven expertise in genomic analysis, including analysis of high throughput whole exome, whole genome, and targeted sequencing data, as well as chip-typing data, association analysis, genome sequence analysis, experimental design and statistical analysis. Related experience in genomic analyses, knowledge of online tools and databases for genetic analyses, and experience in statistical analyses of large datasets is also required. The position will also require significant cross functional responsibilities, communicating results and findings to key stakeholders in research and clinical, as well as senior management and collaborators.

• Oversee the evaluation of cohorts and research projects for feasibility of genetic studies and leading experimental design strategies across a breadth of genetics study designs including multiplex families, trios, population extremes (including super controls), case-control studies, imputation, as well as others
• Oversee a variety of statistical genetics analyses of studies for both complex and Mendelian diseases (e.g. linkage, family based association studies, genome wide association studies, next generation sequence analysis, gene x gene interactions, gene x environment interactions)
• Provide expertise in developing workflows and analysis pipelines for projects that involve customized arrays, exome, and/or whole genome sequencing data. Provide statistical genetics expertise required for algorithm development and other analyses related to variant calling, variant filtering and annotation, as well as sophisticated association and burden test analyses
• Interact with biostatisticians, epidemiologists and clinical scientists to carry out statistical data programming and genetics data analysis
• Advise other researchers in the design of experiments and the analysis of genetic data
• Oversee the preparation of scientific presentations, manuscripts, reports, and grant proposals including the preparation of tables, figures, and graphs depicting research results


Experience and Required Skills:
• Qualified candidates should have a PhD in Biostatistics, Genetics, Statistics, Genetic epidemiology, Quantitative genetics, Biocomputing, Bioinformatics or related field or Master's Degree with equivalent level of experience in statistical analysis of high throughput genome sequence and genotype data. PhD or MS with at least 5+ years of experience in human genetics research with clinical genetics preferred. Minimum of 2 years of supervisory experience is expected.
• Experience with handling & managing data/software associated with high-throughput instruments for genetics/genomics. Statistical knowledge and experience as well as strong background in computer programming
• Strong knowledge in use of statistical software (e.g. R, SAS, Perl etc.), with ability to perform statistical analysis, interpret, and effectively communicate results
• Documented experience in development of computational algorithms in statistical genetics. Develops, codes and tests new methods and applications
• Experience in software development is highly desirable, preferably using CIC+
• Record of publishing in peer-reviewed journals
• Fluency in programming (Java, Perl, C, BioPerl in Unix/Linux environment) for applications in computational biology and statistical genetics
• Fluency with genome databases (such as those relating to genome annotation, genetic variants, and metabolic pathways) and biological & statistical software packages (such as gene annotation programs, R and Plink) that are relevant for the study of computational genetics and genomics
• Experience in large-scale analysis of next generation DNA sequencing data (e.g. whole exome and whole genome) as well as array based genotype data
• Desired skills include experience in statistical genetics, R, BioConductor, Perl, with knowledge of QC and management of large genomic datasets generated by microarrays and high throughput sequencing

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