Biostatistician Lead
Listed on 2026-08-15
-
Research/Development
Data Scientist -
IT/Tech
Data Scientist, Data Analyst
What You Will Do
Guidehouse is seeking a Biostatistics Lead to provide technical leadership and oversight across statistical analysis, study methodology, surveillance analytics, program evaluation, and research efforts within our Health AI/Data practice. This individual will serve as the senior statistical authority responsible for ensuring methodological rigor, analytical quality, reproducibility, and scientific defensibility across complex public health and healthcare analytics initiatives. The Biostatistics Lead will collaborate closely with epidemiologists, data scientists, informaticists, and client stakeholders to guide statistical approaches, review analytical products, and support evidence-based decision making.
- Serve as the lead biostatistical advisor across surveillance, research, evaluation, and advanced analytics initiatives.
- Lead development of statistical methodologies, Statistical Analysis Plans (SAPs), analytic protocols, sampling approaches, weighting methodologies, and population estimation strategies.
- Provide technical oversight and peer review for statistical analyses, analytic code, modeling approaches, assumptions, and interpretation of findings.
- Design and oversee complex analyses of surveillance, survey, claims, clinical, registry, laboratory, and other real-world health datasets.
- Guide methodological decisions related to study design, causal inference, quasi-experimental methods, observational studies, and evaluation frameworks.
- Lead development and validation of statistical models, surveillance indicators, outcome measures, performance metrics, and population-level estimates.
- Partner with epidemiologists, researchers, and data scientists to translate research and policy questions into statistically rigorous analytic approaches.
- Evaluate and address methodological considerations including bias, confounding, missing data, selection effects, variance estimation, and statistical uncertainty.
- Review and approve statistical deliverables, technical reports, publications, presentations, and dissemination products prior to release.
- Lead interpretation and communication of statistical findings to technical, scientific, operational, and executive stakeholders.
- Mentor and provide technical leadership to biostatisticians, epidemiologists, analysts, and data scientists.
- Contribute to proposal development, solution design, thought leadership, and business development activities requiring advanced statistical expertise.
- Role is contingent upon contract award
Data Science & Analysis
Travel RequiredUp to 10%
Clearance RequiredAbility to Obtain Public Trust
What You Will DoGuidehouse is seeking a Biostatistics Lead to provide technical leadership and oversight across statistical analysis, study methodology, surveillance analytics, program evaluation, and research efforts within our Health AI/Data practice. This individual will serve as the senior statistical authority responsible for ensuring methodological rigor, analytical quality, reproducibility, and scientific defensibility across complex public health and healthcare analytics initiatives. The Biostatistics Lead will collaborate closely with epidemiologists, data scientists, informaticists, and client stakeholders to guide statistical approaches, review analytical products, and support evidence-based decision making.
- Serve as the lead biostatistical advisor across surveillance, research, evaluation, and advanced analytics initiatives.
- Lead development of statistical methodologies, Statistical Analysis Plans (SAPs), analytic protocols, sampling approaches, weighting methodologies, and population estimation strategies.
- Provide technical oversight and peer review for statistical analyses, analytic code, modeling approaches, assumptions, and interpretation of findings.
- Design and oversee complex analyses of surveillance, survey, claims, clinical, registry, laboratory, and other real-world health datasets.
- Guide methodological decisions related to study design, causal inference, quasi-experimental methods, observational studies, and evaluation frameworks.
- Lead development and validation of statistical models, surveillance indicators, outcome…
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