Senior Analyst - Statistician

About the Company

Curana Health is a national leader in value-based care, dedicated to improving the health, happiness, and dignity of older adults. We provide senior living communities and skilled nursing facilities with solutions—including on-site primary care services, Accountable Care Organizations, and Medicare Advantage Special Needs Plans—proven to enhance health outcomes, streamline operations, and create new financial opportunities. Founded in 2021, we now serve over 200,000 seniors in 1,500+ communities across 32 states, with a team of 1,000+ clinicians and professionals. Ranked #147 on the Inc. 5000 list of America's fastest-growing private companies, we are committed to delivering high-quality, proactive care for seniors.

About the Role

We are seeking a Senior Analyst - Statistician to join our Population Health Operations team. In this role, you will leverage healthcare data, statistical methods, and observational research to measure the real-world impact of Curana’s clinical programs and shape value-based care strategy. This is an opportunity for a research-minded analytics professional who enjoys working with claims, EHR, CMS, MSSP, ACO, or other large-scale healthcare datasets and wants to see their work influence clinical outcomes, utilization, cost of care, and strategic decision-making.

The ideal candidate is comfortable applying statistical methods to practical healthcare questions and translating results into actionable insights for stakeholders.

Why Join Curana Health

• Work on high-impact analyses that directly inform care delivery, outcomes, utilization, and cost of care.
• Apply rigorous statistical methods to real-world healthcare questions in a growing value-based care organization.
• Collaborate with clinical, operational, analytics, and executive stakeholders who use your work to guide strategy and decision-making.
• Contribute to meaningful proof points that support Curana’s mission to improve health outcomes for seniors.
• Join a small, collaborative team where your expertise will be visible, valued, and connected to meaningful decisions.

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.

Requirements

Required Qualifications:

• 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.
• 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.

Preferred Qualifications:

• Master’s or PhD in Statistics, Biostatistics, Epidemiology, Public Health, Health Economics, Data Science, or a related field.
• 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.