Biostatistician

Position Summary

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.

• Develop statistical analysis plans for observational studies, RCTs, quasi‑experimental designs, and community health evaluations.
• Conduct power and sample‑size calculations.
• Advise investigators on appropriate statistical methods and study designs.
• Guide selection of measures, variables, and coding structures.

• Oversee data extraction, cleaning, validation, and merging/linkage from EHR systems, REDCap datasets, and multi‑site data sources.
• Build reproducible data pipelines (R, SAS, Stata, SQL).
• Convert raw datasets into analysis‑ready formats, consistent with workflows.
• Ensure compliance with HIPAA, DUAs, IRB requirements, and internal research SOPs.

• Conduct descriptive, inferential, and multivariable modeling (e.g., LMM, GEE, logistic/Poisson regression, survival analysis).
• Perform longitudinal, clustered, and multi‑level modeling used in community health research.
• Produce tables, figures, and visualizations for internal and external dissemination.
• Collaborate with investigators to interpret and contextualize findings.

• Contribute to research protocols, IRB submissions, and methodological sections of grant proposals.
• Provide biostatistical expertise during project planning, execution, and reporting phases.
• Support multi‑site research implementation activities.
• Submit and lead grant proposals.

• Prepare analytic reports for leadership, funders, and research partners.
• Contribute to and lead peer‑reviewed manuscripts, abstracts, and conference presentations.
• Translate quantitative findings into clear, actionable insights for diverse audiences.

• Work closely with researchers, clinicians, data analysts, technical teams, and community health centers.
• Participate in and lead research meetings.
• Provide statistical consultation and capacity‑building across the research network.

• Doctoral degree in Biostatistics, Statistics, Epidemiology, or related quantitative field.
• Demonstrated expertise in statistical programming (R, SAS, Stata, or Python).
• Experience with large health datasets, longitudinal data, and applied analysis in clinical or public health settings.
• Strong understanding of epidemiologic methods, statistical modeling, and research design.
• Experience working in multi‑site or community‑based research environments.

• Experience with EHR‑derived data and community health center environments.
• Familiarity with REDCap, SQL, and large‑scale data infrastructure.
• Experience contributing to federally funded research (NIH, CDC, HRSA).
• Experience working on RCTs or complex multi‑level studies, as seen in NCPCR/CEAL protocols.
• Geographic Information Systems (GIS) experience is a plus.