Full-Time: Bioinformatician (Hybrid)

Required Skills & Qualifications:

·         Masters/PhD degree in Biostatistics, Informatics, or related field of study. Bioinformatics major preferred.

·         One to two years of bioinformatics, biostatistics, or statistics experience.

·         Requires proficiency with JMP, SAS, R, or other statistical software.

·         Experience with next-generation biological datasets such as ATACseq, RNAseq, DNAseq, etc.

·         Experience applying statistical analysis and machine learning algorithms.

·         Experience with data wrangling and data visualization.

·         Experience with building *nix system bash pipeline.

·         Experience with markdown and version control systems.

·         Experience in biochemistry, algorithms/complexity theory, biostatistics, and bioinformatics.

·         Strong statistical background of various analytic methodologies such as hypothesis testing, regression, model selection, generalized linear models, PCA, cluster analysis, and meta-analysis.

·         Ability to handle large-scale data manipulation, analysis, and interpretation of results.

·         Solid computational skills to build data models and develop reusable scripts/packages/applications using R, Python, SAS or other statistical and/or mathematical programming packages.

·         Ability to work as a member of a team. 

·         Ability to work well under pressure and meet multiple and sometimes conflicting deadlines.

·         Ability to interact in an appropriate and professional manner.

·         Demonstrated cooperative behavior and positive problem solving and conflict resolution skills.

·         Available to work dependable, flexible shift.

 

Description of Duties:

·         Conduct statistical analyses using statistical software and summarize results for publication/grants using Word, Excel, and PowerPoint.

·          Work with internal investigators to design studies and interpret results of statistical analyses and obtain and manage large datasets.

·          Create reproductible markdown reports detailing data cleaning, processing, normalization, analysis, and visualization.

·          Apply statistic and machine learning algorithms to derive biological meaning from data.

·         Process and analyze genome, metagenome, and transcriptome data.

·         Pathway and gene functional analysis.

·         Extracting and working with large public databases of biological data (e.g., NCBI).

·         Stay up to date with the current and accepted methods for platform-specific data processing and analysis.

·         Data wrangling and data manipulation.

·         Data organization and version control.

·         Other duties as may be assigned.

Salary Range: $90,000-$120,000