Bristol-Myers Squibb Company

Bioinformatics Statistician / Machine Learning Expert

Cambridge, MA, United States
May 30, 2019
Required Education
Position Type
Full time
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.

Job Description:

We are seeking a highly motivated bioinformatician with academic and/or industry experience to join our Cambridge MA Translational Bioinformatics group. The successful candidate will use advanced analytical methods to identify mechanisms of resistance to cancer therapies using integrated analyses of genomic datasets from multiple clinical studies and multiple technologies including transcriptomics, metabolomics, proteomics and gene expression. You will collaborate with experts in oncology, drug discovery and genomic technologies inside and outside of BMS to develop and test hypotheses about resistance to current cancer therapies and develop new approaches to benefit patients

  • Collaborate closely with bioinformaticians, biologists and other scientists to evaluate, develop, and apply cutting-edge methods for integrated analysis of genomic datasets across preclinical studies, clinical trials, and real-world evidence to identify subgroups of drug-resistant tumors
  • 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

  • Ph.D. in statistics, biostatistics, Computer Scienceor a related discipline
  • Solid grounding in statistical theory and familiarity with recent developments in statistics
  • Demonstrated expertise in integrating datasets from multiple genomic platforms and patient cohorts
  • Working knowledge of cancer biology or immunology
  • 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
  • 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