Director of Stat Methodology role will drive projects developing methodological solutions to statistical innovation problems identified by Data and Quantitative Science (DQS) and the broader Drug Development organization.
Responsibilities
- Active engagement with stakeholders and driving development of statistical methods and research.
- Providing statistical consulting to specific projects.
- Overseeing development of tools and software to implement methodological solutions.
- Mentoring and coaching junior members of the team.
- Drive formulation, development and implementation of innovative novel statistical analysis methods and innovative study designs across therapeutic areas.
- Facilitates discussions, translates scientific questions into statistical terms, and statistical concepts into layman terms.
- Influence stakeholders by communicating effectively the findings of their project-driven research to cross-functional teams; provides interpretation of scientific results in a manner accessible to non-statisticians.
- Function as statistical lead on statistical topics influencing and advising senior leadership on issues that have business impact.
- Continually develop technical knowledge of statistical methodology and build BMS external scientific reputation via publications and presentations.
- Continually enhance knowledge of drug development process, regulatory and commercial requirement.
- Develop more junior stat methodologists by providing mentorship and coaching as well as developing training curriculum for the broader DQS organization.
- Effectively communicate the DQS Mission and Vision in a fashion that generates pride, excitement and commitment within DQS.
- Enable a culture of inclusiveness, respect for diversity, compliance with process and allow for the questioning and challenging of others in a respectful and constructive manner.
- Leadership is a required component of this position – engage with Biostatisticians and other cross-functional team members to drive development of innovative statistical methods for emerging trial design and analytics problems.
Qualifications
- Ph.D. in Statistics, Biostatistics, or Data Science with 9+ years of experience in Pharmaceutical Research & Development or academia/government.
- Solid understanding of drug development with proven track record of leading statistical innovation.
- Deep expertise in one of the following scientific topics (with proven publication records) and working knowledge of the others: Bayesian methods; Adaptive design; Real-world evidence; Advanced predictive modelling; Machine learning; Decision analysis.
- Ability to summarize technically/analytically complex information for a non-technical audience.
- Demonstrated ability to work in a team environment with good interpersonal, communication, writing, and organizational skills.
- Ability to organize multiple work assignments and establish priorities.
Applicants can request a reasonable workplace accommodation or adjustment prior to accepting a job offer. If you require reasonable accommodations in completing this application or in any part of the recruitment process, direct your inquiries to adastaffingsupport@bms.com.
eeo accessibility to access our complete Equal Employment Opportunity statement.
