Principal Scientist, Predictive Sciences
Posted on Apr 6, 2021 by Bristol-Myers Squibb
At Bristol Myers Squibb, we are inspired by a single vision - transforming patients' lives through science. In oncology, hematology, immunology and cardiovascular disease - and one of the most diverse and promising pipelines in the industry - each of our passionate colleagues contribute to innovations that drive meaningful change. We bring a human touch to every treatment we pioneer. Join us and make a difference.
Seeking a collaborative and innovative scientist to join the Predictive Sciences team in the San Francisco Bay Area. This person will help advance Bristol Myers Squibb's oncology pipeline using machine learning, network analysis, and translational bioinformatics approaches on multi-omics data from internal, public, and real-world data. They will conduct analyses and help craft experiments to prioritize drug targets, enable patient selection strategies, and guide drug development decisions. Finally, this person must connect with colleagues across the organization to influence R&D from target discovery through early-stage development.
Lead computational biology efforts on multi-disciplinary teams
Deliver results and recommendations from analysis of high-dimensional datasets (eg, RNA-seq, WES, single-cell sequencing) to guide programs in pre-clinical drug discovery and development
Collaborate with computational researchers, statisticians, biologists, and translational teams to develop and implement analyses that expedite our pipeline
Develop and apply computational tools to build predictive models that can illuminate biological mechanisms of resistance to standard of care and enable patient stratification
Communicate findings and recommend follow-up actions in multiple settings (including: 1:1, seminars, group and project meetings)
PhD in bioinformatics, computational biology, computer science, engineering, statistics, genetics, or similar with 5+ years of industry experience.
Proven track record of contributing to and helping advance multi-disciplinary team projects.
Expertise with a high-level programming language such as R or Python for sophisticated data analysis and reproducible research practices.
Proficiency integrating and analyzing diverse high-dimensional, omics data sets relevant for the intersection of immunology, stromal, and tumor biology.
Capability to conduct detailed analyses to evaluate therapeutic hypotheses and prioritize clinically-relevant questions.
Scientific curiosity with an ability to identify questions bioinformatics approaches can address, and the skills to develop solutions both independently and collaboratively.
Excellent problem-solving skills and teamwork.
Strong communication, data presentation, and visualization skills.
Background in oncology/immuno-oncology and/or experience working with clinical trial or real-world data is a plus.