The Lead Statistician & Program Evaluator leads the design, analysis, and interpretation of quantitative and
qualitative data to inform strategic decisions across Central Health’s healthcare delivery system. This role combines
advanced biostatistical modeling, program evaluation, and community health assessment expertise with strong
communication and presentation skills to translate complex findings into actionable insights for diverse audiences,
from executive leadership and clinicians to community partners.
As a member of the Data Insights & Innovation team, the Lead Statistician & Program Evaluator partners with
analysts, data scientists, engineers, and healthcare leaders to develop models that predict patient risk, assess
health outcomes and equity, and evaluate the effectiveness of programs across the Central Health system.

Design and implement advanced healthcare models (e.g., risk stratification, utilization forecasting, quality/outcome measurement) using Python and SQL.
Creates data visualizations using available applications (e.g. Tableau, MS Excel, ArcGIS)
Develop and validate predictive models and statistical algorithms to evaluate health interventions and clinical programs.
Ensure methodological rigor in analyses supporting health equity, access, and outcomes measurement.
Leverage literature (e.g. journal articles, white papers, etc.) and other publicly available data resources related to data requests to inform analysis when appropriate.
Lead formal evaluations of clinical, community, and population health programs to assess effectiveness, efficiency, and impact.
Design evaluation frameworks, metrics, and data collection instruments aligned with program logic models and strategic objectives.
Apply mixed-methods approaches to evaluate both quantitative outcomes and qualitative findings.
Develop surveys for patients, providers, and community stakeholders to capture health behaviors, needs, and
satisfaction; training operations and clinical teams on survey administration.
Ensure survey validity, reliability, and compliance with research ethics standards.
Lead and contribute to community health assessments and needs analyses to identify disparities, gaps in care, and
opportunities for improvement.
Integrate findings with secondary data sources (e.g., BRFSS, ACS, CDC, SEER) for comprehensive community profiling.
Present analytic results and recommendations clearly to varied audiences including executives, community boards, clinicians, and policymakers.
Translate complex statistical findings into accessible insights for strategic and operational decision-making.
Author technical reports, white papers, and evaluation summaries suitable for publication or public presentation.
Partner with the Principal Data Scientist and other data professionals to strengthen Central Health’s analytic capabilities and data science maturity.
Provide mentorship to analysts and evaluation specialists in statistical methods and program evaluation best practices.
Provides statistical modeling expertise for various projects.
Performs other duties as assigned

Master's Degree (higher degree accepted) in Mathematics, Statistics, Computer Engineering, Epidemiology, or Data Analytics field.
Required
Doctoral or Professional Degree in Biostatistics, Epidemiology, Health Services Research, or a related field. Preferred

Work Experience

5 years Experience conducting statistical analysis and program evaluation in a healthcare, public health, or research setting.
Required
2 years Demonstrated experience with healthcare data sources (claims, EHR, quality metrics, SDOH data). Required
2 years Experience with Python scripting. Required
2 years Experience with SQL scripting. Required
1 year Familiarity with cloud-based data environments
(Azure, Snowflake) and modern data pipelines. Preferred