Phd Causal Inference Jobs in Ohio (NOW HIRING)

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

• Must be a U.S. Citizen or Permanent Resident. and ability to obtain and maintain a Public Trust clearance.

• Master's degree or PhD in Biostatistics, Statistics, Epidemiology (quantitative focus), Mathematics, or related quantitative discipline.

• EIGHT (8) or more years of professional experience applying advanced biostatistical methods within public health, healthcare, surveillance, clinical research, life sciences, or population health environments.

• Experience serving as a lead statistician, technical lead, senior reviewer, or methodological advisor for complex analytics, surveillance, evaluation, or research initiatives.

• Experience in statistical inference, hypothesis testing, study design, power analysis, sample size determination, variance estimation, and population-level inference.

• Experience in applying advanced statistical methodologies including generalized linear models, mixed-effects models, multilevel/hierarchical models, survival analysis, longitudinal modeling, interrupted time series (ITS), difference-in-differences (DiD), propensity score methods, causal inference techniques, survey-weighted analyses, variance estimation, missing data methods, sensitivity analyses, and population-level estimation.

• Experience designing and analyzing studies utilizing complex survey designs, including stratification, clustering, weighting, nonresponse adjustment, and variance estimation.

• Experience in statistical programming using SAS and at least one additional statistical language such as R or Python.

• Experience developing and reviewing Statistical Analysis Plans (SAPs), methodology documents, study protocols, publication-quality analyses, and scientific manuscripts.

• Experience reviewing analytic code, statistical outputs, and analytical approaches for methodological accuracy, reproducibility, and scientific rigor.

• Experience working with large-scale surveillance, claims, clinical, registry, laboratory, electronic health record (EHR), or observational health datasets.

• Experience leading technical workstreams and mentoring multidisciplinary analytic teams.

• PhD in Biostatistics, Statistics, Epidemiology, or related quantitative discipline.

• Strong understanding of epidemiologic methods and application of biostatistics to surveillance, public health research, and program evaluation.

• Proven ability to communicate complex statistical concepts and findings to both technical and non-technical audiences.

• Experience serving as lead statistician or senior methodological reviewer for large public health, healthcare, or research programs.

• Experience with Bayesian statistical methods, hierarchical Bayesian modeling, machine learning, predictive modeling, or AI-enabled analytics.

• Experience conducting real-world evidence (RWE) studies using observational healthcare datasets.

• Experience supporting federal public health agencies, healthcare organizations, or biomedical research programs.

• Experience developing weighting methodologies and population estimation approaches for surveillance, survey, or public health studies.

• Experience supporting peer-reviewed scientific publications and conference presentations.

• Experience with cloud analytics environments such as Databricks, Snowflake, Azure, AWS, or Palantir Foundry.

• Experience supporting SAS-to-R or SAS-to-Python migration and statistical validation efforts.

• Experience with HIV surveillance processes and data.

• Experience working with state public health agencies.

• Experience leading multidisciplinary analytic teams in consulting, research, or government environments.