The Data Analyst – Care Delivery is an individual contributor responsible for transforming complex operational and healthcare data into actionable insights via reports and self-service dashboards. These insights help clinical leaders manage day-to-day operations, drive improvement and deliver greater health outcomes for our members and clients. Reporting to the Director of Clinical Insights, this role serves as the primary analytical engine supporting care delivery reporting, clinical stratification, engagement channel performance, and population health strategy. You will partner closely with Care Delivery Nursing, Quality and Health Impact leaders to design and deliver sophisticated analyses and self-service reporting that enables data-driven decision-making at every level of the organization. 

Key Accountabilities 

• Operational Dashboard Development (60%): Design, build, and maintain a suite of Tableau dashboards/reports that provide real-time visibility into clinical operational efficiency and ops success metrics. Partner with the Director of Clinical Insights and clinical operational leaders to define, build, validate, and evolve the KPIs that matter most to our staff, members, and customers. Respond to strategic analytical questions from clinical leadership regarding staffing models, resource capacity, and engagement channel effectiveness. 
• Clinical Quality & Audit Support (20%):  Build and maintain automation required for Quality Standards in alignment with our Customer Audit requirements. Write advanced SQL queries across complex, multi-source datasets and synthesize findings into clear, concise executive-ready narratives, and build dashboards when appropriate to enable self-service. 
• Health Impact Analytics (20%): Support the refinement and validation of predictive models used for member targeting and clinical program design. Collaborate with technical and clinical stakeholders to assess model effectiveness and recommend methodology improvements. Respond to strategic analytical questions from leadership regarding Performance Guarantee (PG) attainment. 

A Day In The Life  

• Deliver high-quality, self-service Tableau reporting that empowers clinical and operational leaders to monitor performance and act on insights without analytical dependency. 
• Support clinical stratification methodology by analyzing member behavior data, claims history, and engagement patterns to identify and prioritize actionable populations. 
• Partner cross-functionally with Product, Technology, and Clinical leaders to ensure data assets accurately reflect operational realities and support channel optimization goals. 
• Monitor and report on Clinical Performance Guarantees (PGs), proactively surfacing trends, anomalies, and root causes to support remediation planning. 
• Contribute to the documentation of data workflows, metric definitions, and analytical methodologies to support organizational knowledge transfer and audit readiness. 

What We Are Looking For 

Education & Experience 

• Education: Bachelor's degree in Statistics, Mathematics, Health Informatics, Computer Science, Business, or a related quantitative field required; Master's degree preferred. 
• Experience: 5+ years of progressive experience in data or business analytics, with meaningful exposure to healthcare operations, clinical data, or population health environments. 

Technical Skills 

• Visualization: Expert-level proficiency in Tableau; ability to architect and build interactive, self-service dashboards with governance and scalability in mind. 
• Query & Data Engineering: Advanced SQL scripting (T-SQL, PL/SQL) with demonstrated ability to navigate complex relational schemas, medical claims databases, and multi-source data environments. 
• Cloud & Big Data: Hands-on experience with cloud-based data warehouses (Amazon Redshift preferred); familiarity with Big Data environments (Hadoop/Hive) a plus, along with experience with Databricks architecture. 
• Advanced Analytics: Applied experience with predictive modeling, cohort matching, statistical analysis, or machine learning frameworks in a healthcare or operational context. 
• Productivity & Modeling: High proficiency in Excel for rapid prototyping and ad-hoc modeling; Python a plus. 
• UAT/QA: Experience in performing UAT/QA processes to ensure accurate, user-friendly reporting and dashboard outputs  

Domain Knowledge 

• Working knowledge of medical claims data structures, clinical performance metrics, and operational drivers of healthcare cost and utilization. 
• Familiarity with population health concepts including care gap identification, member risk stratification, and engagement channel performance measurement. 
• Understanding of Clinical Performance Guarantees (PGs) and how analytics supports attainment and remediation planning. 

Professional Competencies 

• Analytical Rigor: Strong pattern recognition and problem-solving skills; comfortable working with large, complex, and sometimes ambiguous datasets to surface meaningful signals. 
• Stakeholder Communication: Proven ability to translate technical methodology and analytical findings into clear, actionable narratives for non-technical clinical and operational audiences. 
• Initiative & Ownership: Self-starter with a "roll up your sleeves" mindset; able to manage multiple concurrent workstreams with minimal supervision in a fast-paced environment. 
• Collaboration: Effective cross-functional collaborator in a matrixed organization; able to manage competing stakeholder needs and priorities with professionalism and clarity. 
• Attention to Detail: High degree of accuracy in data validation, metric definition, and reporting output — recognizing that analytical errors in a clinical context carry real operational consequence.