Senior Manager of Statistical Analysis and Quality Control

OVERVIEW

Hendall is currently seeking a Senior Manager of Statistical Analysis and Quality Control to serve as the senior statistical, quality control, and behavioral health data lead on a project team supporting the U.S. Department of Health and Human Services (HHS). This is a senior management role with responsibility for technical leadership, independent review, and quality assurance of complex analyses and data products.

The ideal candidate will have strong quantitative, data processing, and analytic skills and extensive experience applying population-based statistical methods to large, complex datasets, including administrative and survey data. The Senior Manager will lead rigorous statistical analyses and guide statisticians, data analysts, and other professionals; establish and enforce quality control standards, review analytic work produced by project staff, support AI-enabled analytics, and ensure that methods, results, data files, reports, and dissemination products are accurate, reproducible, consistent, timely, and publication-ready.

The Senior Manager of Statistical Analysis and Quality Control will provide senior-level technical leadership across statistical analysis, data processing, reporting, and quality control activities. The Senior Manager will establish QC expectations, direct and conduct independent validation of analyses, serve as a senior technical reviewer, and coordinate analytic work across a fast-paced, complex project. This role requires both hands-on analysis and senior-level oversight, including guiding staff, tracking task status and priorities, resolving data quality and methodology issues, and ensuring that deliverables meet established analytic, reporting, schedule, and QC standards.

Specifically:

• Lead and conduct univariate, bivariate, and multivariate statistical analyses to describe populations, assess relationships, identify trends, and answer research and programmatic questions; provide senior statistical guidance on analytic design and interpretation
• Formulate and test hypotheses using appropriate inferential statistical methods, including regression-based approaches, analysis of variance, confidence intervals, model diagnostics, sensitivity analyses, and trend analysis, to answer research and programmatic questions; provide senior guidance on analytic design, interpretation, and statistical appropriateness
• Lead analyses of cross-sectional and longitudinal data, including repeated observations, linked records, and trend data, and review the interpretation of changes in populations and outcomes over time
• Analyze and oversee analyses of large administrative and survey datasets using population-based statistical methods to produce reliable estimates, rates, proportions, and other measures for reporting and decision-making
• Use statistical, machine learning, and AI-enabled data analytics techniques to identify patterns, improve analytic workflows, support automated anomaly detection, and solve complex data problems; independently validate AI- and machine-learning-assisted outputs for accuracy, reproducibility, and appropriate interpretation
• Lead quality control reviews of data files, statistical programs, calculations, tables, figures, and reports; independently reproduce key results, investigate discrepancies, verify analytic logic and assumptions, and work with stakeholders to resolve data quality and methodology issues before release
• Establish, document, implement, and continuously improve formal quality control procedures, review checklists, issue-resolution processes, and QC documentation for statistical analyses, data processing, and dissemination reports and datasets
• Lead quality control reviews of data files, statistical programs, calculations, tables, figures, visualizations, dashboards, reports, and technical documentation; independently reproduce key results, verify analytic logic and assumptions, investigate discrepancies, and determine whether products are ready for release
• Develop and independently review SAS programs for statistical analyses, quality checks, ad hoc data runs, and reproducible analytic workflows; review code prepared by others and use R, Python, STATA, or other tools as appropriate for data manipulation, analysis, visualization, and automation
• Oversee special data analyses, feasibility studies, data mining and exploration, and ad hoc data requests; prepare or review clear write-ups, tables, figures, summaries, and data products that translate complex…