Biostatistician, School of Medicine
Methodist University
Methodist University Cape Fear Valley Health School of Medicine, located in the vibrant and diverse community of Fayetteville, NC, is poised for growth and innovation as a candidate school with the LCME, with a start date of summer 2026 for its charter class. Our mission is bold yet vital: to prepare the next generation of socially accountable, equity-focused, community-engaged physician leaders committed to reducing health disparities and improving outcomes in southeastern North Carolina and beyond. We are looking for a proactive, resourceful, self-directed, and highly organized biostatistician with experience in data science and/or epidemiological methods. The statistician will report to the Associate Dean of Research and is expected to work with both faculty and students on the design, analysis, and dissemination of research projects. In addition, the statistician will contribute to teaching as well as supporting our office of student assessment.
Qualified candidates are invited to submit:
• A letter of application;
• Curriculum vitae;
• A concise equity and diversity statement about research, teaching, or other experiences, successes, and challenges in working with diverse investigators and student; and
• Contact information for three references.
- Collaborating with faculty to design and conduct research projects.
- Mentoring students and provide technical guidance on study design, data analysis, and manuscript preparation.
- Contributing to dissemination of research findings including conference abstracts, presentations, and manuscripts for publication.
- Contributing to developing grant proposals.
- Teaching research and biostatistical concepts in the medical curriculum.
- Supporting the Office of Assessment in data analytics, visualization, and reporting related to student learning, curriculum evaluation, and institutional effectiveness.
- Other duties as assigned
- Master's degree in (bio)statistics or related field and 2 years relevant experience. Demonstrated contributions to significant projects or additional doctoral education may substitute for experience.
- Proven proficiency in at least one statistical programming language, such as SAS or R.
- Experience processing and analyzing large, multi-source datasets, with the ability to execute statistical analyses, develop analytical reports, and maintain high-quality documentation on time.
- Excellent oral and written communication skills
- Knowledge of data modeling and additional specialized software (e.g. SQL, Python).
- Broad understanding of medical physiology, anatomy, and processes to be able to give consultative services across various medical disciplines.
- Contributing to clinical research projects, manuscript preparation or other written summaries of results.
- Collaborating with professionals who have various levels of statistical understanding.
- Teaching and mentoring professional/graduate level students.
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