Biostatistics Senior Analyst - PREVENT Institute

The Ohio State University

12d

About The Position

The PREVENT Institute (Prevention Research, Equity, Value, Early Detection, Navigation and Translation) seeks a highly skilled Statistics and Biostatistics Analyst 3 to provide advanced statistical leadership and analytic expertise for prevention science, population health, implementation science, cancer prevention and control, health equity, survivorship, screening, and early detection research. This senior quantitative scientist designs, analyzes, interprets, and disseminates complex research studies while collaborating with multidisciplinary teams of investigators, clinicians, implementation scientists, data scientists, and community-engaged researchers. The Analyst 3 provides independent biostatistical consultation and leadership across federally funded and foundation-supported research projects. The position supports the PREVENT Institute’s mission to generate actionable evidence that improves population health outcomes and accelerates implementation of effective prevention and screening interventions in real-world settings. It also contributes innovative analytic approaches to inform policy, healthcare delivery, and public health practice, with a focus on population data, advanced analytics, prevention research, and evidence-based interventions.

Requirements

Bachelor’s degree or equivalent experience.
At least 4 years of relevant experience.
Advanced proficiency in statistical programming software, including SAS and R.
Demonstrated experience collaborating on externally funded research projects.
Experience developing statistical analysis plans and independently conducting complex analyses.

Nice To Haves

Master’s degree in Biostatistics, Statistics, Epidemiology, Data Science, Public Health, Health Services Research, Applied Mathematics, or a related quantitative field.
Six years of progressively responsible experience in biostatistical analysis, population health research, implementation science, or related quantitative research.
PhD in Biostatistics, Statistics, Epidemiology, Health Services Research, Data Science, or a related field.
Experience supporting NIH, PCORI, ACS, CDC, AHRQ, or other federally funded grants.
Expertise in implementation science methodologies and frameworks.
Experience with EHR, registry, claims, and large population-based datasets.
Record of peer-reviewed publications in population health, implementation science, cancer prevention, or health services research.
Experience mentoring junior investigators and research personnel.

Responsibilities

Provide advanced statistical consultation for clinical, translational, behavioral, implementation, health services, population health, and community-based research studies.
Design and implement complex statistical analysis plans for prospective and retrospective research studies.
Lead analytic strategies for large observational studies, pragmatic trials, implementation studies, hybrid effectiveness-implementation designs, and community-engaged research.
Apply methods including longitudinal analysis, multilevel modeling, survival analysis, generalized linear mixed models, causal inference, mediation analysis, and predictive modeling.
Develop approaches for evaluating implementation outcomes, dissemination strategies, and health equity interventions.
Collaborate on multidisciplinary research teams and contribute to grant applications, including statistical sections, power analyses, sample size calculations, data analysis plans, and methodological approaches.
Contribute to study design and protocol development and advise investigators on analytic approaches that strengthen funding competitiveness.
Design and conduct analyses using electronic health record, cancer registry, administrative claims, survey, and community-based data.
Evaluate implementation outcomes, including adoption, reach, fidelity, sustainability, acceptability, feasibility, and effectiveness.
Support population health initiatives in cancer prevention, screening, survivorship, chronic disease prevention, and health disparities.
Develop analytic approaches to evaluate healthcare delivery interventions and population-level outcomes, and translate findings into recommendations for healthcare systems, policymakers, and community organizations.
Lead development of complex research databases and analytic datasets; conduct data quality assessments and validation; and create reproducible analytic workflows.
Develop programming solutions using SAS, R, STATA, Python, SQL, and other statistical software.
Apply advanced quantitative methods, machine learning, and predictive analytics to large-scale population health datasets.
Ensure data integrity, confidentiality, and regulatory compliance across research activities.
Lead or contribute to peer-reviewed manuscripts, scientific abstracts, presentations, technical reports, methodological publications, and collaborative scientific writing.
Present findings at institutional, regional, national, and international conferences, translating complex statistical findings for scientific and community audiences.
Provide statistical mentorship to faculty, fellows, trainees, junior analysts, and research staff; lead statistical working groups and collaborative analytic initiatives.
Develop standard operating procedures, analytic guidance documents, and best practices, and contribute to strategic planning and growth of the PREVENT Institute’s quantitative research infrastructure.