Role Description
The Biostatistician provides statistical leadership and advanced analytic support for community‑engaged research, clinical trials, program evaluations, and quality‑improvement initiatives. This role ensures methodological rigor; oversees data cleaning, merging, and preparation; performs complex statistical analyses; and collaborates with multidisciplinary teams across HCN and partner institutions to generate valid, actionable insights that advance health equity.
Key Responsibilities
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Statistical Design & Methodology
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Develop statistical analysis plans for observational studies, RCTs, quasi‑experimental designs, and community health evaluations.
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Conduct power and sample‑size calculations.
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Advise investigators on appropriate statistical methods and study designs.
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Guide selection of measures, variables, and coding structures.
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Data Management & Quality Assurance
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Oversee data extraction, cleaning, validation, and merging/linkage from EHR systems, REDCap datasets, and multi‑site data sources.
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Build reproducible data pipelines (R, SAS, Stata, SQL).
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Convert raw datasets into analysis‑ready formats, consistent with workflows.
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Ensure compliance with HIPAA, DUAs, IRB requirements, and internal research SOPs.
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Statistical Analysis & Interpretation
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Conduct descriptive, inferential, and multivariable modeling (e.g., LMM, GEE, logistic/Poisson regression, survival analysis).
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Perform longitudinal, clustered, and multi‑level modeling used in community health research.
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Produce tables, figures, and visualizations for internal and external dissemination.
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Collaborate with investigators to interpret and contextualize findings.
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Research & Grant Support
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Contribute to research protocols, IRB submissions, and methodological sections of grant proposals.
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Provide biostatistical expertise during project planning, execution, and reporting phases.
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Support multi‑site research implementation activities.
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Submit and lead grant proposals.
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Reporting, Publication & Dissemination
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Prepare analytic reports for leadership, funders, and research partners.
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Contribute to and lead peer‑reviewed manuscripts, abstracts, and conference presentations.
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Translate quantitative findings into clear, actionable insights for diverse audiences.
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Collaboration & Stakeholder Engagement
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Work closely with researchers, clinicians, data analysts, technical teams, and community health centers.
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Participate in and lead research meetings.
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Provide statistical consultation and capacity‑building across the research network.
Qualifications
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Doctoral degree in Biostatistics, Statistics, Epidemiology, or related quantitative field.
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Demonstrated expertise in statistical programming (R, SAS, Stata, or Python).
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Experience with large health datasets, longitudinal data, and applied analysis in clinical or public health settings.
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Strong understanding of epidemiologic methods, statistical modeling, and research design.
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Experience working in multi‑site or community‑based research environments.
Preferred Qualifications
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Experience with EHR‑derived data and community health center environments.
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Familiarity with REDCap, SQL, and large‑scale data infrastructure.
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Experience contributing to federally funded research (NIH, CDC, HRSA).
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Experience working on RCTs or complex multi‑level studies, as seen in NCPCR/CEAL protocols.
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Geographic Information Systems (GIS) experience is a plus.