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RemoteFull-timeStaff / PrincipalAnalyst
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This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior/Principal Statistician (RWE) based in United States.
This is a senior-level statistical role focused on real-world evidence, clinical and non-clinical research, and the delivery of high-quality statistical programming and analysis.
You will provide scientific and statistical leadership while supporting complex studies and translating analytical requirements into robust deliverables.
The role combines hands-on programming expertise with leadership, quality oversight, governance, and stakeholder communication.
You will work with complex datasets, statistical analysis plans, and industry standards including CDISC SDTM and ADaM.
The position offers a highly collaborative remote environment where experienced statisticians can contribute to challenging projects and develop new capabilities.
You will also help guide colleagues, strengthen analytical practices, and ensure work meets demanding quality and timeline expectations.
The successful candidate will bring strong technical judgment, scientific curiosity, and the ability to influence teams across complex research programs.
Provide senior statistical and scientific expertise across clinical and non-clinical research and real-world evidence projects.
Support the development and execution of complex statistical analyses, ensuring outputs are scientifically sound, accurate, and delivered within established timelines.
Develop post-hoc analysis plans that enable programmers to implement formal analyses and required outputs.
Review and interpret Statistical Analysis Plans (SAPs), output shells, datasets, and analysis requirements to guide programming activities.
Apply CDISC implementation standards, including SDTM and ADaM, to support consistent and high-quality data structures and analytical outputs.
Provide leadership and mentorship to statistical programming and analysis teams, supporting knowledge sharing and professional development.
Contribute to quality, compliance, governance, and continuous improvement across statistical and analytical activities.
Review complex deliverables and provide technical guidance to ensure accuracy, consistency, and adherence to applicable standards.
Communicate statistical findings, requirements, risks, and recommendations clearly to technical and non-technical stakeholders.
Collaborate closely with colleagues in a supportive team environment, sharing expertise and helping others develop new skills.
Contribute to complex efficacy analyses and other advanced analytical activities where appropriate.
MSc or higher in Statistics, Mathematics, or a closely related quantitative discipline.
PhD or higher in Statistics, Mathematics, or a related field is advantageous.
Strong statistical programming experience, including proficiency with SAS/BASE, SAS/STAT, SAS/GRAPH, and ODS functionality.
Knowledge of additional programming or statistical languages is advantageous.
Strong working knowledge of CDISC standards, particularly SDTM and ADaM.
Demonstrated ability to develop post-hoc analysis plans and translate statistical requirements into clear programming specifications.
Experience working with Statistical Analysis Plans, output shells, complex datasets, and advanced analytical requirements.
Previous leadership or team-development experience, with the ability to mentor colleagues and provide technical direction.
Experience working with complex efficacy analyses is highly desirable.
Strong understanding of statistical methodology, scientific principles, data quality, and research processes.
Excellent analytical and problem-solving abilities with strong attention to detail.
Effective communication skills and the ability to influence and collaborate across multidisciplinary teams.
A proactive, collaborative, and learning-oriented approach, with a willingness to share knowledge and support colleagues.
Ability to work independently in a fully remote environment while maintaining effective collaboration with globally distributed teams.
Availability to work within a schedule that provides sufficient overlap with US working hours.
Fully remote, full-time working arrangement.
Flexible working hours designed to support work-life balance.
Opportunity to contribute to complex clinical, non-clinical, and real-world evidence research.
Career development and mentorship opportunities.
Continuous learning and opportunities to expand technical and scientific expertise.
Supportive, collaborative, and knowledge-sharing team culture.
Opportunity to work on projects with meaningful implications for healthcare and life sciences.
Global working environment with exposure to multidisciplinary statistical and data science teams.