Principal Scientist, Integrated Sciences and Translational Bioinformatics, Immuno-Oncology
About the Job
About Bristol-Myers Squibb\: Bristol-Myers Squibb is a global biopharmaceutical company whose mission is to discover, develop and deliver innovative medicines that help patients prevail over serious diseases. One shared journey is moving us forward at Bristol-Myers Squibb. Around the world, we are passionate about making an impact on the lives of patients with serious disease. Empowered to apply our individual talents and ideas so that we can learn and grow together. And driven to make a difference, from innovative research to hands-on community support. Bristol-Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees the resources to pursue their goals, both at work and in their personal lives. We are seeking a highly motivated bioinformatician with significant academic and/or industry experience to join our Integrated Science and Translational Bioinformatics Immuno-Oncology teams. The mandate of the Integrated Science group is to integrate, synthesize and analyze internal and external data that address defined translational questions of fundamental importance to the field of Immune-Oncology (IO) so to generate actionable scientific insights, hypotheses, and recommendations for stakeholders across the enterprise. The successful candidate will help execute this mandate through the strategic application of cutting edge bioinformatics approaches. The candidate will internally face and interact with scientists within Discovery, Biomarker Science, Translational Biology, Clinical Development, Medical Affairs and Commercial organizations and will externally face and interact with academic investigators globally as a major scientific collaborator. Responsibilities · Analysis of various –omic-scale data including RNA-Seq, Exome and Whole Genome Sequencing, single cell sequencing, and high throughput proteomics in order to nominate novel drug targets, enable patient enrichment strategies, understand mechanisms of resistance to IO therapies and prioritize combination therapies. · Integration and mining of large scale external data sets (TCGA, 1KG, EXAC, Cosmic) to further our understanding of the relationship between tumor genetics, the tumor microenvironment, and response to therapies. · Evaluate and analyze exploratory genomics data from clinical trials to understand drug mechanisms and patient response. · Perform integrated- and meta-analyses of –omic data across multiple clinical trials. · Extract insights and generate hypotheses to be evaluated in future trials and to inform our discovery pipeline. · Collaborate with bioinformaticians, statisticians, biologists, and clinicians to identify critical questions that can be addressed via computational approaches. · Design, lead, and manage complex computational research projects. · Help define our bioinformatics strategy to advance BMS’ Oncology/Immuno-Oncology pipeline. Enterprise Mindset\: The ability to make decisions, set priorities and share resources based on what will benefit the whole. Capable of building and maintaining networks within and outside of the organization.Qualification:
Ph.D. in bioinformatics, engineering, statistics, physics, molecular biology, genetics, or a similar discipline.
Ten (10) or more year’s relevant experience in tumor biology, tumor immunology and/or drug discovery in an academic, pharma or biotech setting.
Proven track record designing, leading, and managing complex computational research projects.
Experience working in complex, matrixed organizations expected; experience leading projects in a matrixed environment preferred.
Strong background in -omic (DNA, RNA, epigenetic, proteomic) data analysis and biological interpretation.
Experience working with data from clinical trials is expected.
Solid background in Oncology and Immuno-Oncology biology.
Ability to communicate effectively with biologists, biostatisticians computational and clinical scientists.
Proficiency using R and Bioconductor packages, at least one scripting language (Python, Perl), and SQL .
Experience working with Linux high performance compute clusters and cloud based computing platforms (Amazon EC2).
Fluency in NGS experiments and data analysis (e.g. GATK, Cufflinks, SAMtools, BAMtools etc.) is expected.
Working knowledge of commercial and publicly available biological databases including NCBI, Ensembl, ArrayExpress/GEO, SRA, TCGA, 1000 Genomes etc.).
Strong verbal and written communication skills, with the ability to analyze and present data in a clear professional format to computational, bench, and clinical scientists.
Experience working with thought leaders and leading scientific collaborations is essential.