We are seeking an innovative scientist to join our Bioinformatics Methodology team in the Translational Bioinformatics group. This group of computational scientists is responsible for advancing Bristol-Myers Squibb’s industry-leading pipeline in multiple therapeutic areas (including Immuno-Oncology, Cardiovascular, Fibrosis, and Immunoscience) through the strategic application of cutting-edge bioinformatics approaches. The scientists in this group analyze real-world health data, design experiments and analyze both pre-clinical and clinical -omics data sets, including RNA-Seq, Exome and Whole Genome Sequencing, single-cell sequencing, high-throughput proteomics, and multiplex flow cytometry in order to nominate novel drug targets, enable patient enrichment strategies, and guide drug development decisions. The group interacts with and influences all aspects of R&D at BMS, from early discovery through late-stage development.
· Collaborate closely with others on translational research teams to evaluate, develop, and apply cutting-edge methods for analysis of real-world and digital health data and multi-modal, high-dimensional -omics data
· Influence best practices in areas such as causal inference and building and assessing predictive models using very large data sets
· Provide expertise in state-of-the-art statistical methods for data exploration, visualization, and analysis while both advising colleagues and performing hands-on work
· Ph.D. in statistics, biostatistics, or statistical epidemiology
· Solid grounding in statistical theory and familiarity with recent developments in statistics
· Skilled at working with large collections of observational, e.g. public health, data
· Expertise in causal inference, resampling methods, modern classification and regression, analysis of longitudinal data, predictive model development and assessment, and statistical graphics and programming
· Working knowledge of biology
· Familiarity with statistical genetics and genomics and clinical trial design and analysis is a plus
· Fluency with Linux-based high-performance computing environments, R/Bioconductor, and reproducible research practices
· Strong problem-solving and collaboration skills, and rigorous and creative thinking
· Excellent written and oral communication skills, including an ability to discuss and explain complex ideas with computational scientists, experimentalists, and clinicians
· The ability to work across organizations to define and solve problems that will benefit the whole. Capable of establishing strong working relationships across the organization.
· Enjoy collaborating to solve challenging problems at the intersection of modern statistics and medicine to help bring new medicines to patients