Biostatistician II | Job Code 21-017
Biostatistician II sought by Lundquist Institute for Biomedical Innovation in Torrance, CA.
Duties: Conduct biostatistical and genetic analyses, interpret results, and generate reports for biomedical and genetics research. Implement statistical methods, develop novel statistical packages, and create usable scripts/macros using appropriate programming languages. Apply statistical methods and machine learning algorithms to analyze diverse, heterogeneous data, such as SNP data, DNA methylation data, metabolomics data, lipidomics data and RNA-sequence data. Provide statistical expertise in the design of experiments and studies, research proposal development, sample size determination, statistical procedures recommendation, and plans for interim reviews and final analysis in collaboration with principal investigators and researchers. Identify, evaluate, and incorporate relevant analytical methods/pipelines/applications for novel research data. Explore innovative quality control procedures, advanced computational methods, algorithms and analysis pipelines to enhance research and discovery of biomarkers obtained from genomic, methylomic, transcriptomic and proteomic platforms. Write reusable R scripts and SAS macros for data cleaning, analyzing, and summarizing. Provide tabular and written summaries or analyses in a form suitable for inclusion in project deliverables, publications, grant proposals, as well as media for presentation at project meetings. Present statistical methodologies and interpret analysis results to researchers and collaborators on a regular basis. Provide statistical consultation to principal investigators, researchers, students and fellows. Provide training and workshops for R programming, advanced statistical models, and data analysis tools/pipelines.
Requirements: Master’s degree, or equivalent, in Biostatistics, Statistics, or a related field, plus two (2) years of Biostatistics, Genetic Statistics, Statistics, or related experience: conducting biostatistical and genetic analyses; designing, constructing, and maintaining statistical database programs and databases; interpreting results and generating reports for biomedical and genetics research; preparing database and software program documentation; contributing in the preparation of grant proposals, publications, and presentations; running statistical software packages such as SAS, R, and PLINK; utilizing programming languages including Perl and C++; and working in both Windows and Linux environments.