Note: The job is a remote job and is open to candidates in USA. Curana Health is a value-based care organization focused on improving health outcomes for older adults. The Senior Analyst - Statistician will design and execute observational healthcare research, analyze large-scale clinical and utilization datasets, and evaluate the impact of clinical programs. The role translates statistical findings into actionable insights for clinical, operational, financial, and executive stakeholders.
Responsibilities
- Design and execute observational research studies, including matched cohort analyses and other quasi-experimental approaches
- Evaluate the impact of clinical programs and interventions on outcomes such as utilization, cost of care, readmissions, avoidable utilization, quality outcomes, and CMS-related performance measures
- Develop statistically sound approaches to reduce bias and confounding in healthcare datasets
- Define cohorts, inclusion and exclusion criteria, comparison groups, exposure groups, and outcome measures aligned with study objectives
- Extract, clean, structure, and analyze large healthcare datasets, including claims, EHR, ACO, CMS, and MSSP data
- Build reproducible analytic datasets and workflows using SQL, Python, and other statistical programming tools
- Translate statistical findings into clear, actionable insights, reports, summaries, and visualizations for clinical, operational, financial, and executive stakeholders
- Partner with clinical leaders, analytics, data engineering, operations, product, and leadership teams to define study questions, interpret results, and apply findings
- Use AI-enabled tools, where appropriate, to improve analytic efficiency and support tasks such as feature generation, covariate selection, and workflow improvement
Skills
- Minimum of 3 years of experience in healthcare analytics, outcomes research, applied statistics, biostatistics, epidemiology, or a related analytical/research environment
- Bachelor's degree required; advanced degree in Statistics, Biostatistics, Epidemiology, Public Health, Health Economics, Data Science, or a related field preferred
- Master's Degree or PhD in Statistics, Biostatistics, Epidemiology, Public Health, Health Economics, Data Science, or a related field is required
- Experience working with healthcare datasets such as claims, EHR, CMS, MSSP, ACO, or other large-scale clinical, utilization, or cost data
- Strong proficiency with Python and SQL
- Experience applying statistical methods to evaluate programs, outcomes, utilization, cost of care, readmissions, avoidable utilization, quality outcomes, or related healthcare performance measures
- Ability to communicate complex analytical findings clearly to technical and non-technical stakeholders
- Advanced degree in Statistics, Biostatistics, Epidemiology, Public Health, Health Economics, Data Science, or a related field preferred
- Experience with observational research, matched cohort studies, causal inference, propensity score methods, or frameworks for addressing bias and confounding
- Experience in value-based care, ACOs, population health, post-acute care, long-term care, health plans, academic research, university research, or similar research-focused environments
- Experience with R, SAS, Databricks, or AI-enabled coding and analytics tools such as Claude Code or Microsoft Copilot
- Experience developing publication-quality tables, executive summaries, manuscripts, internal reports, or external-facing research materials
Benefits
- Join a small, collaborative team where your expertise will be visible, valued, and connected to meaningful decisions.
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