Senior Manager, Real-World Data Research

Position overview: The Senior Manager, Real-World Data Research (RWDR) leads non-interventional research projects in support of medical, HEOR and other customer groups for International Markets (Europe, APAC and rest of world). This is an individual contributor role responsible for identifying data sources, contributing to study design, overseeing programming, analysis and summary of data, and collaborating with stakeholders on interpretation and presentation of results. You will contribute to RWDR team and departmental initiatives to optimize and innovate real-world data research.Key Responsibilities

Conduct thorough data analysis and oversee programming of statistical analyses; deliver results to customers in appropriate formats; assist with follow-up questions and interpretation of results.Identify appropriate data sources for research objectives; acquire and store data for projects.Collaborate with customers on study concept development, protocol and Statistical Analysis Plan (SAP) writing, and dissemination (e.g., abstracts, manuscripts).Communicate results effectively, orally and in writing.Manage complex work environments, balancing demands from multiple customers to execute projects.Make sound scientific decisions based on data, analysis and experience.Work across diverse therapeutic areas, assets, study designs and data sources.Qualifications and Experience

Advanced degree in a quantitative discipline such as biostatistics, epidemiology or related field.Pharmaceutical and/or Epidemiology/Outcomes Research experience.Required Knowledge and Competencies

Deep understanding of secondary and/or primary patient data sources for real-world research and analysis.Ability to analyze observational data for pharmaco-epidemiology, outcomes research, and market research.Ability to effectively manage research projects and communicate study objectives, methods and findings.Proficient in SAS/R programming; GitHub experience is a plus.Ability to write or critically review the scientific content and analytical sections of protocols, SAPs, final reports and dissemination materials.Ability to apply statistical methods to real-world studies (e.g., survival analysis, logistic/multivariate regression); knowledge of machine learning methods (e.g., clustering, prediction, NLP) is a plus.Additional Information

BMS is committed to equal employment opportunity and providing reasonable accommodations in our recruitment process. Applicants can request accommodations prior to accepting an offer. For inquiries, contact adastaffingsupport@bms.com. See our EEO statement at careers.bms.com/eeo-accessibility. Covid-19 vaccination guidance is per company policy. BMS will consider applicants with arrest and conviction records as allowed by law. Data processed in accordance with data privacy policies.

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