Computational Biologist

Booz Allen Hamilton•Boston, MA

1d•Hybrid

About The Position

Computational Biologist The Opportunity: Provide statistical and computational analysis capabilities for large genetic datasets. Develop and execute research plans involving analysis of large-scale multi-omics data. Document and disseminate best practices and methods for genomic analysis. Present data and results in client meetings and in scientific forums. Write manuscripts, abstracts, and white papers. You Have: Experience with programming in R or Python Experience with statistical and computational analysis of genomic data Knowledge of human genomic data and common open-source genomic analysis tools Ability to independently conduct analysis, report results, and draw conclusions Ability to communicate complex concepts clearly and concisely to management, clients, researchers, and on-site staff Ability to quickly digest new concepts and apply them Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements Doctorate degree in Genetics, Computational Biology, Statistics, Bioinformatics, or Biomedical Engineering Nice If You Have: Experience conducting analyses in high-performance computing environments Experience with Next Generation Sequencing or array genotype data Experience with large population cohorts, including the UK Biobank and All of Us Experience with data standardization and harmonization for clinical Electronic Health Records Experience working with controlled vocabularies and conducting large-scale phenome-wide association studies and genome-wide association studies analysis Experience with multi-omics data analysis, machine learning methods, and statistical modeling Vetting: Applicants selected will be subject to a government investigation and may need to meet eligibility requirements of the U.S. government client. 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Requirements

Experience with programming in R or Python
Experience with statistical and computational analysis of genomic data
Knowledge of human genomic data and common open-source genomic analysis tools
Ability to independently conduct analysis, report results, and draw conclusions
Ability to communicate complex concepts clearly and concisely to management, clients, researchers, and on-site staff
Ability to quickly digest new concepts and apply them
Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements
Doctorate degree in Genetics, Computational Biology, Statistics, Bioinformatics, or Biomedical Engineering

Nice To Haves

Experience conducting analyses in high-performance computing environments
Experience with Next Generation Sequencing or array genotype data
Experience with large population cohorts, including the UK Biobank and All of Us
Experience with data standardization and harmonization for clinical Electronic Health Records
Experience working with controlled vocabularies and conducting large-scale phenome-wide association studies and genome-wide association studies analysis
Experience with multi-omics data analysis, machine learning methods, and statistical modeling

Responsibilities

Provide statistical and computational analysis capabilities for large genetic datasets.
Develop and execute research plans involving analysis of large-scale multi-omics data.
Document and disseminate best practices and methods for genomic analysis.
Present data and results in client meetings and in scientific forums.
Write manuscripts, abstracts, and white papers.