Biostatistician III

Duke Careers•Durham, NC

18d•$101,968 - $164,762•Onsite

About The Position

The School of Nursing Health Statistics and Data Science Core is seeking a collaborative and analytically driven Biostatistician III to join our research team. In this role, you will serve as a key statistical partner to faculty investigators, supporting a broad portfolio of research studies and funded projects that advance nursing science, healthcare outcomes, and population health. You will independently manage multiple projects while providing expert statistical consultation, advanced data analysis, programming support, and interpretation of research findings. This position offers an exciting opportunity to work alongside nationally recognized faculty and researchers, contributing to high-impact research from study design through publication. You will play an integral role in developing statistical analysis plans, conducting sophisticated analyses, preparing manuscripts and grant applications, and helping ensure scientific rigor across research initiatives. As a Biostatistician III, you will have the opportunity to apply advanced statistical methods, collaborate on interdisciplinary research teams, and continuously expand your expertise by learning and implementing innovative analytical approaches. You will also support the School's educational mission through statistical consultation and workshops for faculty, students, and research staff.

Requirements

Doctoral degree in (bio) statistics or related field and no relevant experience, OR Master's degree in (bio) statistics or related field and 2 years relevant experience, OR Bachelor's degree in (bio) statistics or related field and 4 years relevant experience.
Demonstrated experience contributing to clinical trials, clinical research studies, or other research projects involving statistical analysis.
Experience preparing statistical reports, academic manuscripts, abstracts, presentations, or other written summaries of analytical results.
Thorough experience with R and SAS programming.
Strong written and verbal communication skills, including the ability to explain statistical concepts to non-statistical audiences.
Strong knowledge of R and SAS programming and statistical methodologies.
Working knowledge of SPSS, Stata, Mplus, Tableau, Excel, Access, or other data management, visualization, and analytical systems.
Ability to manage multiple projects simultaneously while meeting competing deadlines.
Ability to work effectively with diverse interdisciplinary teams, investigators, and external collaborators.
Strong attention to detail and commitment to data quality, reproducibility, and scientific integrity.

Nice To Haves

Master's degree in (bio) statistics or closely related field and two or more years of relevant experience.
Experience working with extramural grants and contracts.
Experience supporting federally funded or industry-sponsored research projects.
Experience serving as a lead statistician on clinical research studies or clinical trials.
Experience conducting latent variable modeling.
Experience contributing to peer-reviewed publications and grant applications.
Experience mentoring, training, or providing guidance to junior staff, students, or collaborators.
Experience using artificial intelligence (AI) tools or methodologies to support data analysis and research activities.
Proficiency with R and/or Python and other statistical or data visualization platforms.

Responsibilities

Develop, implement, and document statistical analysis plans for clinical, behavioral, health services, and other research studies conducted within the School of Nursing.
Perform and interpret a wide range of statistical analyses, including advanced analytical techniques, with minimal supervision while independently recommending appropriate additional analyses as research questions evolve.
Provide statistical consultation to principal investigators, faculty researchers, research coordinators, and study teams regarding study design, methodology, sample size considerations, data management, and interpretation of results.
Write, validate, troubleshoot, and optimize R and/or SAS programs used for data preparation, statistical analyses, reporting, and visualization.
Explore AI capabilities to make the research process more efficient.
Develop analysis datasets by integrating data from multiple sources, ensuring accuracy, consistency, and compliance with study protocols and reporting requirements.
Evaluate alternative programming and analytical approaches to improve efficiency, accuracy, and overall quality of research deliverables.
Identify potential data quality issues through analytical review and collaborate with investigators and research personnel to resolve discrepancies and ensure data integrity.
Prepare comprehensive statistical reports, data summaries, tables, figures, and presentations for investigators, sponsors, and research stakeholders.
Draft and contribute statistical content for abstracts, manuscripts, technical reports, presentations, grant proposals, progress reports, and study documentation.
Collaborate closely with faculty statisticians and investigators to ensure study results and conclusions are presented accurately, objectively, and without bias.
Participate in all phases of assigned projects, including study planning, analysis execution, dissemination of findings, publication development, and grant support.
Establish project timelines, forecast effort requirements, monitor progress, and proactively communicate project status to investigators and faculty statisticians.
Monitor project scope and identify potential out-of-scope activities, ensuring proper communication and resource planning.
Build and maintain productive working relationships with investigators, faculty statisticians, clinical research personnel, students, government agencies, industry sponsors, and external collaborators.
Learn and apply emerging statistical methodologies and analytical techniques to improve research quality and expand service capabilities.
Deliver educational workshops, seminars, and training sessions to School of Nursing faculty, staff, and students on statistical methods, data analysis, and research best practices.
Support the mission of the Health Statistics and Data Science Core by promoting methodological rigor, reproducible research practices, and collaborative scientific inquiry.
Perform other related duties incidental to the work described herein.