Senior Principal Scientist, Computational Biology

Bristol Myers Squibb
Cambridge, Massachusetts, US
Jul 24, 2021
Aug 06, 2021
Biology, Statistics
Employment Type
Full time
Salary Type
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.
We seek a creative and passionate computational scientist to join the Predictive Sciences group. As part of the Immunology, Cardiovascular, & Fibrosis (ICF) team within Predictive Sciences, you would be responsible for advancing Bristol Myers Squibb's early discovery pipeline for autoimmune and inflammatory diseases through the application of systems immunology to high-dimensional multimodal data.
Responsibilities will include, but are not limited to, the following:
- Provide scientific leadership, strategic oversight, and technical guidance for preclinical projects in partnership with immunology discovery teams
- Apply systems biology and related approaches to position discovery programs relative to exisiting therapies (e.g. differentiation from standard-of-care, design of combination therapies)
- Mentor team members through direct reporting relationships and leadership of matrix teams
- Collaborate with teams of multi-disciplinary scientists to define and execute analysis plans to address scientific questions using internal and external omics datasets
- Communicate findings and recommend follow up actions in multiple settings (including 1:1, seminars, project meetings, and external publications)
The ideal candidate will have the following mix of professional and personal characteristics:
- PhD in computational biology, bioinformatics, statistics, computer science/math/engineering or a related field
- 10 or more years relevant research experience, preferred
- Background in immunology and/or experience with autoimmune diseases
- Expertise in mathematical modeling of complex biological systems to generate actionable insights from high-dimensional molecular datasets (e.g. sc/bulk RNAseq and proteomics)
- Advanced hands-on knowledge of at least one high-level programming language such as R or Python for data analysis and reproducible research practices
- Demonstrated ability to advance multi-disciplinary team projects required; managerial and mentorship experience preferred
- Scientific curiosity with an ability to identify questions bioinformatics approaches can address, and the skills to develop solutions both independently and collaboratively
Around the world, we are passionate about making an impact on the lives of patients with serious diseases. Empowered to apply our individual talents and diverse perspectives in an inclusive culture, our shared values of passion, innovation, urgency, accountability, inclusion and integrity bring out the highest potential of each of our colleagues.
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 with the resources to pursue their goals, both at work and in their personal lives.
Our company is committed to ensuring that people with disabilities can excel through a transparent recruitment process, reasonable workplace adjustments and ongoing support in their roles. Applicants can request an approval of accommodation prior to accepting a job offer. If you require reasonable accommodation in completing this application, or any part of the recruitment process direct your inquiries to Visit to access our complete Equal Employment Opportunity statement.
Company: Bristol Myers Squibb
Req Number: R1541699
Updated: 2021-08-02 06:51:46.488 UTC
Location: Cambridge,Massachusetts
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, age, disability, protected veteran status, pregnancy, citizenship, marital status, gender expression, genetic information, political affiliation, or any other characteristic protected by law.