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Position Summary

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 in support of prevention science, population health, implementation science, cancer prevention and control, health equity, survivorship, screening, and early detection research. The individual will serve as a senior quantitative scientist responsible for the design, analysis, interpretation, and dissemination of complex research studies while collaborating with multidisciplinary teams of investigators, clinicians, implementation scientists, data scientists, and community-engaged researchers.

The Analyst 3 will provide independent biostatistical consultation and leadership across a diverse portfolio of federally funded and foundation-supported research projects. This position will play a critical role in advancing the PREVENT Institute's mission to generate actionable evidence that improves population health outcomes and accelerates the implementation of effective prevention and screening interventions into real-world settings.

Aligned with the PREVENT Institute's focus on population health, prevention, survivorship, implementation science, health services research, predictive analytics, and community-engaged research, the position will support the development of innovative analytic approaches that inform policy, healthcare delivery, and public health practice. The role aligns with PREVENT's emphasis on population data, advanced analytics, prevention research, and implementation of evidence-based interventions.

Primary Responsibilities

Advanced Statistical Leadership

• 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 development of analytic strategies for large observational studies, pragmatic trials, implementation studies, hybrid effectiveness-implementation designs, and community-engaged research.
• Provide expertise in longitudinal analysis, multilevel modeling, survival analysis, generalized linear mixed models, causal inference, mediation analysis, and predictive modeling.
• Develop innovative approaches for evaluating implementation outcomes, dissemination strategies, and health equity interventions.

Research Collaboration and Grant Support

• Serve as a key collaborator on multidisciplinary research teams.
• Participate in the development of NIH, PCORI, ACS, CDC, DOD, AHRQ, and foundation grant applications.
• Develop statistical sections, power analyses, sample size calculations, data analysis plans, and methodological approaches for grant proposals.
• Contribute to study design and protocol development for prevention and implementation science research.
• Assist investigators in identifying innovative analytic approaches that strengthen funding competitiveness.

Population Health and Implementation Science Analytics

• Design and conduct analyses using electronic health record data, cancer registry data, administrative claims data, survey data, and community-based datasets.
• Evaluate implementation outcomes including adoption, reach, fidelity, sustainability, acceptability, feasibility, and effectiveness.
• Support population health initiatives focused on cancer prevention, screening, survivorship, chronic disease prevention, and health disparities.
• Develop analytic approaches to evaluate healthcare delivery interventions and population-level outcomes.
• Collaborate with investigators to translate findings into actionable recommendations for healthcare systems, policymakers, and community organizations.

Data Management and Methodological Innovation

• Lead development of complex research databases and analytic datasets.
• Conduct data quality assessments, validation activities, and reproducible analytic workflows.
• Develop programming solutions using SAS, R, STATA, Python, SQL, and other statistical software.
• Apply advanced quantitative methods, machine learning approaches, and predictive analytics to large-scale population health datasets.
• Ensure data integrity, confidentiality, and regulatory compliance across research activities.

Scholarly Dissemination

• Lead or contribute to peer-reviewed manuscripts, scientific abstracts, presentations, and technical reports.
• Present findings at institutional, regional, national, and international conferences.
• Participate in methodological publications and collaborative scientific writing efforts.
• Translate complex statistical findings into clear language appropriate for scientific and community audiences.

Mentorship and Leadership

• 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.
• Contribute to strategic planning and growth of the PREVENT Institute's quantitative research infrastructure.

Qualifications

Bachelor's degree or equivalent experience. Advanced degree in relevant field may be desirable. 4 years of relevant experience required. 4-8 years of relevant experience preferred. Advanced proficiency in statistical programming software including SAS and R. Demonstrated experience collaborating on externally funded research projects. Experience developing statistical analysis plans and conducting complex analyses independently.

Preferred Qualifications

• Master's degree in Biostatistics, Statistics, Epidemiology, Data Science, Public Health, Health Services Research, Applied Mathematics, or 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 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.

Core Competencies

• Advanced Statistical Analysis
• Biostatistics
• Population Health Research
• Implementation Science
• Health Services Research
• Predictive Modeling and Advanced Analytics
• Research Design and Methodology
• Scientific Communication
• Collaborative Leadership
• Grant Development and Research Support
• Publications

Additional Information:

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