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