Bristol-Myers Squibb Company

Bioinformatics Research Investigator

Hopewell, NJ, US
Apr 12, 2018
Required Education
Position Type
Full time

• Leads and collaborates on analysis and interpretation of large-scale genomics and pharmacogenetic data sets derived from early clinical and translational studies, including data from GWAS and NGS studies (e.g., whole- exome and genome sequencing, RNA sequencing, selected gene panels, single cell RNA sequencing and liquid biopsy data)

• Supports technology and assay development efforts by developing and/or implementing bioinformatics pipelines for various genomic platforms.

• Identify opportunities for improvement of analytical pipelines and data management tools that can enhance data analysis strategies.

• Works closely with Clinical Genetics and Genomics Technology Leads to establish, implement, and execute acceptable QA/QC practices for all data generated.

• Works closely with team to develop experimental plans, validation reports, work instructions, and technology transfer documents.

• Serves as a subject matter expert to biologists, geneticists, clinicians, statisticians, wet lab scientists and other key stakeholders across different functions in the organization, including but not limited to computational genomics, and translational technologies groups.

• Stays current in bioinformatics methods and tools by keeping up with relevant literature and by attending scientific meetings.

• Performs other duties as assigned.


• PhD, PharmD or other advanced degree in genetics, pharmacogenomics, bioinformatics, computer science and/or statistics; or MS with 4 years of relevant pharmaceutical experience in Immuno-Oncology

• 2+ years of experience in pharmaceutical, biotech industries or academic research, working in complex, matrixed environment

• 2+ years of prior research and development experience in Oncology, Immuno-Oncology and Immunosciences is highly desired

• Prior experience using commercial and/or open source analysis tools for quality control, trimming, error correction, and pre-processing of NGS data.

• Prior experience with data analysis and interpretation of NGS large-scale "omics" and "ome" data sets (including genomics, pharmacogenetic, methylome, microbiome, single cell transcriptome, etc.), statistical modeling, and extensive expertise in population genetics and functional genomics.

• Documented experience with molecular assay development, validation, troubleshooting, and analysis of technical data.

• Strong knowledge in use of statistical software, programming languages (e.g., R, SAS, Bioconductor, Python, Perl, Java, Linux) and cloud computing, with ability to perform statistical analysis, interpret, and effectively communicate results.

• Prior experience with analysis of expression and genotyping microarrays.

• Experience with large public and private databases, including 1000g, ESP, EXAC, PharmGKB, ClinVar/ ClinGen etc.