Bristol Myers Squibb Research Investigator, Translational Bioinformatics in Hopewell, New Jersey

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. 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 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.

Responsibilities

  • Collaborate closely with others on translational research teams to evaluate, develop, and apply cutting-edge methods for analysis of multi-modal, high-dimensional -omics data

  • Influence best practices in areas such as causal inference, large-scale inference, building and assessing predictive models, analyzing biological networks, visualizing -omics data, and NGS data normalization and analysis

  • Provide expertise in state-of-the-art statistical methods for data exploration, visualization, and analysis while both advising colleagues and performing hands-on work

Qualifications:

  • Ph.D. in statistics or biostatistics

  • Solid grounding in statistical theory and familiarity with recent developments in statistics

  • Skilled at working with large data sets

  • Expertise in large-scale or causal inference, resampling methods, modern classification and regression, analysis of longitudinal data, predictive model development and assessment, and statistical graphics and programming

  • Familiarity with semi- and non-parametric estimation and inference, survival analysis, multivariate methods, Bayesian statistics, and design of experiments

  • Working knowledge of biology

  • Familiarity with statistical genetics and genomics and clinical trial design and analysis is a plus

  • Experience analyzing and interpreting NGS data 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

Bristol-Myers Squibb is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.